BPQP: A Differentiable Convex Optimization Framework for Efficient End-to-End Learning
Xiao Yang, Xu Yang, Weiqing Liu, Lewen Wang, Jiang Bian
October 2024
Jiang Bian
Senior Principal Research Manager
Publications
Publications by Year
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ElasTST: Towards Robust Varied-Horizon Forecasting with Elastic Time-Series Transformer
Shun Zheng, Xumeng Wen, Jiang Bian
October 2024
IGOR: Image-GOal Representations are the Atomic Control Units for Foundation Models in Embodied AI
Xiaoyu Chen, Junliang Guo, Tianyu He, Chuheng Zhang, Pushi Zhang, Derek Yang, Li Zhao, Jiang Bian
October 2024
Compositional 3D-aware Video Generation with LLM Director
Hanxin Zhu, Tianyu He, Anni Tang, Junliang Guo, Zhibo Chen, Jiang Bian
NeurIPS 2024 | August 2024
LordNet: An efficient neural network for learning to solve parametric partial differential equations without simulated data
Xinquan Huang, Wenlei Shi, Xiaotian Gao, Xinran wei, Jia Zhang, Jiang Bian, Mao Yang, Tie-Yan Liu
Neural Networks | August 2024
Diversification of Adaptive Policy for Effective Offline Reinforcement Learning
Yunseon Choi, Li Zhao, Chuheng Zhang, Lei Song, Jiang Bian, Kee-Eung Kim
IJCAI 2024 | July 2024
NuTime: Numerically Multi-Scaled Embedding for Large-Scale Time Series Pretraining
Chenguo Lin, Xumeng Wen, Wei Cao, Congrui Huang, Jiang Bian, Stephen Lin, Zhirong Wu
Transactions on Machine Learning Research | July 2024
Video In-context Learning
Wentao Zhang, Junliang Guo, Tianyu He, Li Zhao, Linli Xu, Jiang Bian
July 2024
Memories are One-to-Many Mapping Alleviators in Talking Face Generation
Tianyu He, Sheng Zhao, Jiang Bian
IEEE Transactions on Pattern Analysis and Machine Intelligence | June 2024
NaturalSpeech 3: Zero-Shot Speech Synthesis with Factorized Codec and Diffusion Models
Zeqian Ju, Yuancheng Wang, Kai Shen, Xu Tan, Detai Xin, Dongchao Yang, Yanqing Liu, Yichong Leng, Kaitao Song, Siliang Tang, Zhizheng Wu, Tao Qin, Xiang-Yang Li, Wei Ye, Shikun Zhang, Jiang Bian, Lei He, Jinyu Li, Sheng Zhao
ICML | June 2024
Position: Rethinking Post-Hoc Search-Based Neural Approaches for Solving Large-Scale Traveling Salesman Problems
Yifan Xia, Xianliang Yang, Zichuan Liu, Zhihao Liu, Lei Song, Jiang Bian
2024 International Conference on Machine Learning | June 2024
ProbTS: Benchmarking Point and Distributional Forecasting across Diverse Prediction Horizons
Jiawen Zhang, Xumeng Wen, Zhenwei Zhang, Shun Zheng, Jia Li, Jiang Bian
NeurIPS 2024 | June 2024
GAIA: Zero-shot Talking Avatar Generation
Tianyu He, Junliang Guo, Runyi Yu, Yuchi Wang, Jialiang Zhu, Kaikai An, Leyi Li, Xu Tan, Chunyu Wang, HsiangTao Wu, Sheng Zhao, Jiang Bian
2024 International Conference on Learning Representations | May 2024
Whittle Index with Multiple Actions and State Constraint for Inventory Management
Chuheng Zhang, Xiangsen Wang, Wei Jiang, Xianliang Yang, Siwei Wang, Lei Song, Jiang Bian
2024 International Conference on Learning Representations | May 2024
Protecting Your LLMs with Information Bottleneck
Zichuan Liu, Zefan Wang, Linjie Xu, Jinyu Wang, Lei Song, Tianchun Wang, Chunlin Chen, Wei Cheng, Jiang Bian
NeurIPS 2024 | April 2024
RD2Bench: Toward Data-Centric Automatic R&D
Haotian Chen, Xinjie Shen, Zeqi Ye, Xiao Yang, Xu Yang, Weiqing Liu, Jiang Bian
April 2024
MG-TSD: Multi-Granularity Time Series Diffusion Models with Guided Learning Process
Xinyao Fan, Yueying Wu, Chang Xu, Yuhao Huang, Weiqing Liu, Jiang Bian
ICLR 2024 | March 2024
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AUDIT: Audio Editing by Following Instructions with Latent Diffusion Models
Yuancheng Wang, Zeqian Ju, Xu Tan, Lei He, Zhizheng Wu, Jiang Bian, Sheng Zhao
NeurIPS 2023 | December 2023
Near-real-time monitoring of global ocean carbon sink
Piyu Ke, Xiaofan Gui, Wei Cao, Dezhi Wang, Ce Hou, Lixing Wang, Xuanren Song, Yun Li, Biqing Zhu, Jiang Bian, Stephen Sitch, Philippe Ciais, Pierre Friedlingstein, Zhu Liu
December 2023
Distributional Pareto-Optimal Multi-Objective Reinforcement Learning
Xinqiang Cai, Pushi Zhang, Li Zhao, Jiang Bian, Masashi Sugiyama, Ashley J. Llorens
2023 Neural Information Processing Systems | December 2023
BatteryML: An Open-source platform for Machine Learning on Battery Degradation
Han Zhang, Xiaofan Gui, Shun Zheng, Ziheng Lu, Yuqi Li, Jiang Bian
ICLR 2024 | October 2023
Leveraging Large Language Model for Automatic Evolving of Industrial Data-Centric R&D Cycle
Xu Yang, Xiao Yang, Weiqing Liu, Jinhui Li, Peng Yu, Zeqi Ye, Jiang Bian
October 2023
Towards Foundation Models for Learning on Tabular Data
Han Zhang, Xumeng Wen, Shun Zheng, Wei Xu, Jiang Bian
October 2023
DAE-Talker: High Fidelity Speech-Driven Talking Face Generation with Diffusion Autoencoder
Tianyu He, Sheng Zhao, Jiang Bian
ACM International Conference on Multimedia | October 2023
HiFace: High-Fidelity 3D Face Reconstruction by Learning Static and Dynamic Details
Tianyu He, Muscle Wu, Sheng Zhao, Jiang Bian
2023 International Conference on Computer Vision | October 2023
UniAudio: An Audio Foundation Model Toward Universal Audio Generation
Dongchao Yang, Jinchuan Tian, Xu Tan, Rongjie Huang, Songxiang Liu, Xuankai Chang, Jiatong Shi, Sheng Zhao, Jiang Bian, Xixin Wu, Zhou Zhao, Helen Meng
ICML 2024 | September 2023
On the Generalization Properties of Diffusion Models
Puheng Li, Zhong Li, Huishuai Zhang, Jiang Bian
2023 Neural Information Processing Systems | September 2023
Connecting Large Language Models with Evolutionary Algorithms Yields Powerful Prompt Optimizers
Qingyan Guo, Rui Wang, Junliang Guo, Bei Li, Kaitao Song, Xu Tan, Guoqing Liu, Jiang Bian, Yuqing Yang
ICLR 2024 | September 2023
PromptTTS 2: Describing and Generating Voices with Text Prompt
Yichong Leng, Zhifang Guo, Kai Shen, Xu Tan, Zeqian Ju, Yanqing Liu, Yufei Liu, Dongchao Yang, Leying Zhang, Kaitao Song, Lei He, Xiang-Yang Li, Sheng Zhao, Tao Qin, Jiang Bian
ICLR 2024 | September 2023
Learning Pareto-Optimal Policies for Multi-Objective Joint Distribution
Xin-Qiang Cai, Pushi Zhang, Li Zhao, Jiang Bian, Masashi Sugiyama, Ashley J. Llorens
NeurIPS 2023 | September 2023
Robust Situational Reinforcement Learning in Face of Context Disturbances
Jinpeng Zhang, Yufeng Zheng, Chuheng Zhang, Li Zhao, Lei Song, Yuan Zhou, Jiang Bian
Proceedings of the 40th International Conference on Machine Learning (ICML) | September 2023
Pre-Trained Large Language Models for Industrial Control
Lei Song, Chuheng Zhang, Li Zhao, Jiang Bian
ArXiv | August 2023, Vol abs/2308.03028
MuseCoco: Generating Symbolic Music from Text
Peiling Lu, Xin Xu, Chenfei Kang, Botao Yu, Chengyi Xing, Xu Tan, Jiang Bian
June 2023
Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping
Jiyan He, Xuechen Li, Da Yu, Huishuai Zhang, Janardhan (Jana) Kulkarni, Yin Tat Lee, Arturs Backurs, Nenghai Yu, Jiang Bian
International Conference on Learning Representations (ICLR) 2023 | May 2023
Learning Physics-Informed Neural Networks without Stacked Back-propagation
Di He, Wenlei Shi, Shanda Li, Xiaotian Gao, Jia Zhang, Jiang Bian, Liwei Wang, Tie-Yan Liu
AISTATS 2023 | April 2023
NaturalSpeech 2: Latent Diffusion Models are Natural and Zero-Shot Speech and Singing Synthesizers
Kai Shen, Zeqian Ju, Xu Tan, Yanqing Liu, Yichong Leng, Lei He, Tao Qin, Sheng Zhao, Jiang Bian
ICLR 2024 | April 2023
Pointerformer: Deep Reinforced Multi-Pointer Transformer for the Traveling Salesman Problem
Yan Jin, Yuandong Ding, Xuanhao Pan, Kun He, Li Zhao, Tao Qin, Lei Song, Jiang Bian
AAAI 2023 | February 2023
TD3 with Reverse KL Regularizer for Offline Reinforcement Learning from Mixed Datasets
Yuanying Cai, Chuheng Zhang, Li Zhao, Wei Shen, Xuyun Zhang, Lei Song, Jiang Bian, Tao Qin, Tie-Yan Liu
IEEE International Conference on Data Mining (Best Student Paper Runner-Up Awards) | January 2023
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Efficient and Effective Multi-task Grouping via Meta Learning on Task Combinations
Xiaozhuang Song, Shun Zheng, Wei Cao, James Yu, Jiang Bian
2022 Neural Information Processing Systems | November 2022
Learning Differential Operators for Interpretable Time Series Modeling
Yingtao Luo, Chang Xu, Yang Liu, Weiqing Liu, Shun Zheng, Jiang Bian
KDD 2022 | August 2022
Towards Applicable Reinforcement Learning: Improving the Generalization and Sample Efficiency with Policy Ensemble
Zhengyu Yang, Kan Ren, Xufang Luo, Minghuan Liu, Weiqing Liu, Jiang Bian, Weinan Zhang, Dongsheng Li
IJCAI 2022 | July 2022
DEPTS: Deep Expansion Learning for Periodic Time Series Forecasting
Wei Fan, Shun Zheng, Xiaohan Yi, Wei Cao, Yanjie Fu, Jiang Bian, Tie-Yan Liu
ICLR 2022 | April 2022
Multi-Granularity Residual Learning with Confidence Estimation for Time Series Prediction
Min Hou, Chang Xu, Zhi Li, Yang Liu, Weiqing Liu, Enhong Chen, Jiang Bian
WWW 2022 | April 2022
DDG-DA: Data Distribution Generation for Predictable Concept Drift Adaptation
Wendi Li, Xiao Yang, Weiqing Liu, Yingce Xia, Jiang Bian
AAAI 2022 | January 2022
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Mimicking atmospheric photochemical modeling with a deep neural network
Jia Xing, Shuxin Zheng, Siwei Li, Lin Huang, Xiaochun Wang, James T Kelly, Shuxiao Wang, Chang Liu, Carey J. Jang, Yun Zhu, Jia Zhang, Jiang Bian, Tie-Yan Liu, Jiming Hao
Atmospheric Research | December 2021, Vol 265: pp. 105919
ADD: Augmented Disentanglement Distillation Framework for Improving Stock Trend Forecasting
Hongshun Tang, Lijun Wu, Weiqing Liu, Jiang Bian
December 2021
Deep Risk Model: A Deep Learning Solution for Mining Latent Risk Factors to Improve Covariance Matrix Estimation
Hengxu Lin, Dong Zhou, Weiqing Liu, Jiang Bian
ICAIF 2021 | November 2021
Learning Multiple Stock Trading Patterns with Temporal Routing Adaptor and Optimal Transport
Hengxu Lin, Dong Zhou, Weiqing Liu, Jiang Bian
KDD 2021 | August 2021
Exploring deep learning for air pollutant emission estimation
Lin Huang, Song Liu, Zeyuan Yang, Jia Xing, Jia Zhang, Jiang Bian, Siwei Li, Shovan Kumar Sahu, Shuxiao Wang, Tie-Yan Liu
Geoscientific Model Development | July 2021, Vol 14(7): pp. 4641-4654
REST: Relational Event-driven Stock Trend Forecasting
Wentao Xu, Weiqing Liu, Chang Xu, Jiang Bian, Jian Yin, Tie-Yan Liu
2021 The Web Conference | April 2021
Stock Trend Prediction with Multi-granularity Data: A Contrastive Learning Approach with Adaptive Fusion
Min Hou, Chang Xu, Zhi Li, Yang Liu, Weiqing Liu, Enhong Chen, Jiang Bian
CIKM 221 | April 2021
Universal Trading for Order Execution with Oracle Policy Distillation
Yuchen Fang, Kan Ren, Weiqing Liu, Dong Zhou, Weinan Zhang, Jiang Bian, Yong Yu, Tie-Yan Liu
AAAI | February 2021
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Cooperative Policy Learning with Pre-trained Heterogeneous Observation Representations
Wenlei Shi, Xinran Wei, Jia Zhang, Xiaoyuan Ni, Arthur Jiang, Jiang Bian, Tie-Yan Liu
AAMAS 2021 | December 2020
Invertible Image Rescaling
Mingqing Xiao, Shuxin Zheng, Chang Liu, Yaolong Wang, Di He, Guolin Ke, Jiang Bian, Zhouchen Lin, Tie-Yan Liu
16th European Conference Computer Vision (ECCV 2020) | August 2020
Trimming the Sail: A Second-order Learning Paradigm for Stock Prediction
Chi Chen, Li Zhao, Wei Cao, Jiang Bian, Chunxiao Xing
February 2020
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A Divide-and-Conquer Framework for Attention-based Combination of Multiple Investment Strategies
Xiao Yang, Weiqing Liu, Lewen Wang, Cheng Qu, Jiang Bian
2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP) | November 2019
Conservative or Aggressive? Confidence-Aware Dynamic Portfolio Construction
Lewen Wang, Weiqing Liu, Xiao Yang, Jiang Bian
2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP) | November 2019
Demonstration Actor Critic
Guoqing Liu, Li Zhao, Pushi Zhang, Jiang Bian, Tao Qin, Nenghai Yu, Tie-Yan Liu
November 2019
DeepGBM: A Deep Learning Framework Distilled by GBDT for Online Prediction Tasks
Guolin Ke, Zhenhui Xu, Jia Zhang, Jiang Bian, Tie-Yan Liu
KDD '19 Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining | August 2019
Individualized Indicator for All: Stock-wise Technical Indicator Optimization with Stock Embedding
Zhige Li, Derek Yang, Li Zhao, Jiang Bian, Tao Qin, Tie-Yan Liu
25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining | August 2019
Investment Behaviors Can Tell What Inside: Exploring Stock Intrinsic Properties for Stock Trend Prediction
Chi Chen, Li Zhao, Jiang Bian, Chunxiao Xing, Tie-Yan Liu
25th ACM SIGKDD Conference on Knowledge Discover and Data Mining(KDD 2019) | August 2019
A Cooperative Multi-Agent Reinforcement Learning Framework for Resource Balancing in Complex Logistics Network
Xihan Li, Jia Zhang, Jiang Bian, Yunhai Tong, Tie-Yan Liu
AAMAS 2019 | March 2019
Trust Region Evolution Strategies
Guoqing Liu, Li Zhao, Feidiao Yang, Jiang Bian, Tao Qin, Nenghai Yu, Tie-Yan Liu
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence | February 2019
-
Investor-Imitator: A Framework for Trading Knowledge Extraction
Yi Ding, Weiqing Liu, Jiang Bian, Daoqiang Zhang, Tie-Yan Liu
Knowledge Discovery & Data Mining | July 2018
Publications by Research Area
-
IGOR: Image-GOal Representations are the Atomic Control Units for Foundation Models in Embodied AI
Xiaoyu Chen, Junliang Guo, Tianyu He, Chuheng Zhang, Pushi Zhang, Derek Yang, Li Zhao, Jiang Bian
October 2024
ElasTST: Towards Robust Varied-Horizon Forecasting with Elastic Time-Series Transformer
Shun Zheng, Xumeng Wen, Jiang Bian
October 2024
BPQP: A Differentiable Convex Optimization Framework for Efficient End-to-End Learning
Xiao Yang, Xu Yang, Weiqing Liu, Lewen Wang, Jiang Bian
October 2024
Compositional 3D-aware Video Generation with LLM Director
Hanxin Zhu, Tianyu He, Anni Tang, Junliang Guo, Zhibo Chen, Jiang Bian
NeurIPS 2024 | August 2024
LordNet: An efficient neural network for learning to solve parametric partial differential equations without simulated data
Xinquan Huang, Wenlei Shi, Xiaotian Gao, Xinran wei, Jia Zhang, Jiang Bian, Mao Yang, Tie-Yan Liu
Neural Networks | August 2024
Diversification of Adaptive Policy for Effective Offline Reinforcement Learning
Yunseon Choi, Li Zhao, Chuheng Zhang, Lei Song, Jiang Bian, Kee-Eung Kim
IJCAI 2024 | July 2024
NuTime: Numerically Multi-Scaled Embedding for Large-Scale Time Series Pretraining
Chenguo Lin, Xumeng Wen, Wei Cao, Congrui Huang, Jiang Bian, Stephen Lin, Zhirong Wu
Transactions on Machine Learning Research | July 2024
ProbTS: Benchmarking Point and Distributional Forecasting across Diverse Prediction Horizons
Jiawen Zhang, Xumeng Wen, Zhenwei Zhang, Shun Zheng, Jia Li, Jiang Bian
NeurIPS 2024 | June 2024
Memories are One-to-Many Mapping Alleviators in Talking Face Generation
Tianyu He, Sheng Zhao, Jiang Bian
IEEE Transactions on Pattern Analysis and Machine Intelligence | June 2024
NaturalSpeech 3: Zero-Shot Speech Synthesis with Factorized Codec and Diffusion Models
Zeqian Ju, Yuancheng Wang, Kai Shen, Xu Tan, Detai Xin, Dongchao Yang, Yanqing Liu, Yichong Leng, Kaitao Song, Siliang Tang, Zhizheng Wu, Tao Qin, Xiang-Yang Li, Wei Ye, Shikun Zhang, Jiang Bian, Lei He, Jinyu Li, Sheng Zhao
ICML | June 2024
Whittle Index with Multiple Actions and State Constraint for Inventory Management
Chuheng Zhang, Xiangsen Wang, Wei Jiang, Xianliang Yang, Siwei Wang, Lei Song, Jiang Bian
2024 International Conference on Learning Representations | May 2024
GAIA: Zero-shot Talking Avatar Generation
Tianyu He, Junliang Guo, Runyi Yu, Yuchi Wang, Jialiang Zhu, Kaikai An, Leyi Li, Xu Tan, Chunyu Wang, HsiangTao Wu, Sheng Zhao, Jiang Bian
2024 International Conference on Learning Representations | May 2024
Protecting Your LLMs with Information Bottleneck
Zichuan Liu, Zefan Wang, Linjie Xu, Jinyu Wang, Lei Song, Tianchun Wang, Chunlin Chen, Wei Cheng, Jiang Bian
NeurIPS 2024 | April 2024
RD2Bench: Toward Data-Centric Automatic R&D
Haotian Chen, Xinjie Shen, Zeqi Ye, Xiao Yang, Xu Yang, Weiqing Liu, Jiang Bian
April 2024
MG-TSD: Multi-Granularity Time Series Diffusion Models with Guided Learning Process
Xinyao Fan, Yueying Wu, Chang Xu, Yuhao Huang, Weiqing Liu, Jiang Bian
ICLR 2024 | March 2024
AUDIT: Audio Editing by Following Instructions with Latent Diffusion Models
Yuancheng Wang, Zeqian Ju, Xu Tan, Lei He, Zhizheng Wu, Jiang Bian, Sheng Zhao
NeurIPS 2023 | December 2023
Distributional Pareto-Optimal Multi-Objective Reinforcement Learning
Xinqiang Cai, Pushi Zhang, Li Zhao, Jiang Bian, Masashi Sugiyama, Ashley J. Llorens
2023 Neural Information Processing Systems | December 2023
BatteryML: An Open-source platform for Machine Learning on Battery Degradation
Han Zhang, Xiaofan Gui, Shun Zheng, Ziheng Lu, Yuqi Li, Jiang Bian
ICLR 2024 | October 2023
Leveraging Large Language Model for Automatic Evolving of Industrial Data-Centric R&D Cycle
Xu Yang, Xiao Yang, Weiqing Liu, Jinhui Li, Peng Yu, Zeqi Ye, Jiang Bian
October 2023
Towards Foundation Models for Learning on Tabular Data
Han Zhang, Xumeng Wen, Shun Zheng, Wei Xu, Jiang Bian
October 2023
DAE-Talker: High Fidelity Speech-Driven Talking Face Generation with Diffusion Autoencoder
Tianyu He, Sheng Zhao, Jiang Bian
ACM International Conference on Multimedia | October 2023
HiFace: High-Fidelity 3D Face Reconstruction by Learning Static and Dynamic Details
Tianyu He, Muscle Wu, Sheng Zhao, Jiang Bian
2023 International Conference on Computer Vision | October 2023
UniAudio: An Audio Foundation Model Toward Universal Audio Generation
Dongchao Yang, Jinchuan Tian, Xu Tan, Rongjie Huang, Songxiang Liu, Xuankai Chang, Jiatong Shi, Sheng Zhao, Jiang Bian, Xixin Wu, Zhou Zhao, Helen Meng
ICML 2024 | September 2023
On the Generalization Properties of Diffusion Models
Puheng Li, Zhong Li, Huishuai Zhang, Jiang Bian
2023 Neural Information Processing Systems | September 2023
Connecting Large Language Models with Evolutionary Algorithms Yields Powerful Prompt Optimizers
Qingyan Guo, Rui Wang, Junliang Guo, Bei Li, Kaitao Song, Xu Tan, Guoqing Liu, Jiang Bian, Yuqing Yang
ICLR 2024 | September 2023
PromptTTS 2: Describing and Generating Voices with Text Prompt
Yichong Leng, Zhifang Guo, Kai Shen, Xu Tan, Zeqian Ju, Yanqing Liu, Yufei Liu, Dongchao Yang, Leying Zhang, Kaitao Song, Lei He, Xiang-Yang Li, Sheng Zhao, Tao Qin, Jiang Bian
ICLR 2024 | September 2023
Learning Pareto-Optimal Policies for Multi-Objective Joint Distribution
Xin-Qiang Cai, Pushi Zhang, Li Zhao, Jiang Bian, Masashi Sugiyama, Ashley J. Llorens
NeurIPS 2023 | September 2023
Robust Situational Reinforcement Learning in Face of Context Disturbances
Jinpeng Zhang, Yufeng Zheng, Chuheng Zhang, Li Zhao, Lei Song, Yuan Zhou, Jiang Bian
Proceedings of the 40th International Conference on Machine Learning (ICML) | September 2023
Pre-Trained Large Language Models for Industrial Control
Lei Song, Chuheng Zhang, Li Zhao, Jiang Bian
ArXiv | August 2023, Vol abs/2308.03028
MuseCoco: Generating Symbolic Music from Text
Peiling Lu, Xin Xu, Chenfei Kang, Botao Yu, Chengyi Xing, Xu Tan, Jiang Bian
June 2023
Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping
Jiyan He, Xuechen Li, Da Yu, Huishuai Zhang, Janardhan (Jana) Kulkarni, Yin Tat Lee, Arturs Backurs, Nenghai Yu, Jiang Bian
International Conference on Learning Representations (ICLR) 2023 | May 2023
Learning Physics-Informed Neural Networks without Stacked Back-propagation
Di He, Wenlei Shi, Shanda Li, Xiaotian Gao, Jia Zhang, Jiang Bian, Liwei Wang, Tie-Yan Liu
AISTATS 2023 | April 2023
NaturalSpeech 2: Latent Diffusion Models are Natural and Zero-Shot Speech and Singing Synthesizers
Kai Shen, Zeqian Ju, Xu Tan, Yanqing Liu, Yichong Leng, Lei He, Tao Qin, Sheng Zhao, Jiang Bian
ICLR 2024 | April 2023
Pointerformer: Deep Reinforced Multi-Pointer Transformer for the Traveling Salesman Problem
Yan Jin, Yuandong Ding, Xuanhao Pan, Kun He, Li Zhao, Tao Qin, Lei Song, Jiang Bian
AAAI 2023 | February 2023
TD3 with Reverse KL Regularizer for Offline Reinforcement Learning from Mixed Datasets
Yuanying Cai, Chuheng Zhang, Li Zhao, Wei Shen, Xuyun Zhang, Lei Song, Jiang Bian, Tao Qin, Tie-Yan Liu
IEEE International Conference on Data Mining (Best Student Paper Runner-Up Awards) | January 2023
Efficient and Effective Multi-task Grouping via Meta Learning on Task Combinations
Xiaozhuang Song, Shun Zheng, Wei Cao, James Yu, Jiang Bian
2022 Neural Information Processing Systems | November 2022
Towards Applicable Reinforcement Learning: Improving the Generalization and Sample Efficiency with Policy Ensemble
Zhengyu Yang, Kan Ren, Xufang Luo, Minghuan Liu, Weiqing Liu, Jiang Bian, Weinan Zhang, Dongsheng Li
IJCAI 2022 | July 2022
DEPTS: Deep Expansion Learning for Periodic Time Series Forecasting
Wei Fan, Shun Zheng, Xiaohan Yi, Wei Cao, Yanjie Fu, Jiang Bian, Tie-Yan Liu
ICLR 2022 | April 2022
DDG-DA: Data Distribution Generation for Predictable Concept Drift Adaptation
Wendi Li, Xiao Yang, Weiqing Liu, Yingce Xia, Jiang Bian
AAAI 2022 | January 2022
Mimicking atmospheric photochemical modeling with a deep neural network
Jia Xing, Shuxin Zheng, Siwei Li, Lin Huang, Xiaochun Wang, James T Kelly, Shuxiao Wang, Chang Liu, Carey J. Jang, Yun Zhu, Jia Zhang, Jiang Bian, Tie-Yan Liu, Jiming Hao
Atmospheric Research | December 2021, Vol 265: pp. 105919
ADD: Augmented Disentanglement Distillation Framework for Improving Stock Trend Forecasting
Hongshun Tang, Lijun Wu, Weiqing Liu, Jiang Bian
December 2021
Deep Risk Model: A Deep Learning Solution for Mining Latent Risk Factors to Improve Covariance Matrix Estimation
Hengxu Lin, Dong Zhou, Weiqing Liu, Jiang Bian
ICAIF 2021 | November 2021
Learning Multiple Stock Trading Patterns with Temporal Routing Adaptor and Optimal Transport
Hengxu Lin, Dong Zhou, Weiqing Liu, Jiang Bian
KDD 2021 | August 2021
Exploring deep learning for air pollutant emission estimation
Lin Huang, Song Liu, Zeyuan Yang, Jia Xing, Jia Zhang, Jiang Bian, Siwei Li, Shovan Kumar Sahu, Shuxiao Wang, Tie-Yan Liu
Geoscientific Model Development | July 2021, Vol 14(7): pp. 4641-4654
Stock Trend Prediction with Multi-granularity Data: A Contrastive Learning Approach with Adaptive Fusion
Min Hou, Chang Xu, Zhi Li, Yang Liu, Weiqing Liu, Enhong Chen, Jiang Bian
CIKM 221 | April 2021
REST: Relational Event-driven Stock Trend Forecasting
Wentao Xu, Weiqing Liu, Chang Xu, Jiang Bian, Jian Yin, Tie-Yan Liu
2021 The Web Conference | April 2021
Universal Trading for Order Execution with Oracle Policy Distillation
Yuchen Fang, Kan Ren, Weiqing Liu, Dong Zhou, Weinan Zhang, Jiang Bian, Yong Yu, Tie-Yan Liu
AAAI | February 2021
Cooperative Policy Learning with Pre-trained Heterogeneous Observation Representations
Wenlei Shi, Xinran Wei, Jia Zhang, Xiaoyuan Ni, Arthur Jiang, Jiang Bian, Tie-Yan Liu
AAMAS 2021 | December 2020
Trimming the Sail: A Second-order Learning Paradigm for Stock Prediction
Chi Chen, Li Zhao, Wei Cao, Jiang Bian, Chunxiao Xing
February 2020
Conservative or Aggressive? Confidence-Aware Dynamic Portfolio Construction
Lewen Wang, Weiqing Liu, Xiao Yang, Jiang Bian
2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP) | November 2019
A Divide-and-Conquer Framework for Attention-based Combination of Multiple Investment Strategies
Xiao Yang, Weiqing Liu, Lewen Wang, Cheng Qu, Jiang Bian
2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP) | November 2019
Demonstration Actor Critic
Guoqing Liu, Li Zhao, Pushi Zhang, Jiang Bian, Tao Qin, Nenghai Yu, Tie-Yan Liu
November 2019
Individualized Indicator for All: Stock-wise Technical Indicator Optimization with Stock Embedding
Zhige Li, Derek Yang, Li Zhao, Jiang Bian, Tao Qin, Tie-Yan Liu
25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining | August 2019
Investment Behaviors Can Tell What Inside: Exploring Stock Intrinsic Properties for Stock Trend Prediction
Chi Chen, Li Zhao, Jiang Bian, Chunxiao Xing, Tie-Yan Liu
25th ACM SIGKDD Conference on Knowledge Discover and Data Mining(KDD 2019) | August 2019
A Cooperative Multi-Agent Reinforcement Learning Framework for Resource Balancing in Complex Logistics Network
Xihan Li, Jia Zhang, Jiang Bian, Yunhai Tong, Tie-Yan Liu
AAMAS 2019 | March 2019
Trust Region Evolution Strategies
Guoqing Liu, Li Zhao, Feidiao Yang, Jiang Bian, Tao Qin, Nenghai Yu, Tie-Yan Liu
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence | February 2019
Investor-Imitator: A Framework for Trading Knowledge Extraction
Yi Ding, Weiqing Liu, Jiang Bian, Daoqiang Zhang, Tie-Yan Liu
Knowledge Discovery & Data Mining | July 2018
-
Video In-context Learning
Wentao Zhang, Junliang Guo, Tianyu He, Li Zhao, Linli Xu, Jiang Bian
July 2024
Memories are One-to-Many Mapping Alleviators in Talking Face Generation
Tianyu He, Sheng Zhao, Jiang Bian
IEEE Transactions on Pattern Analysis and Machine Intelligence | June 2024
DAE-Talker: High Fidelity Speech-Driven Talking Face Generation with Diffusion Autoencoder
Tianyu He, Sheng Zhao, Jiang Bian
ACM International Conference on Multimedia | October 2023
HiFace: High-Fidelity 3D Face Reconstruction by Learning Static and Dynamic Details
Tianyu He, Muscle Wu, Sheng Zhao, Jiang Bian
2023 International Conference on Computer Vision | October 2023
Invertible Image Rescaling
Mingqing Xiao, Shuxin Zheng, Chang Liu, Yaolong Wang, Di He, Guolin Ke, Jiang Bian, Zhouchen Lin, Tie-Yan Liu
16th European Conference Computer Vision (ECCV 2020) | August 2020
-
Position: Rethinking Post-Hoc Search-Based Neural Approaches for Solving Large-Scale Traveling Salesman Problems
Yifan Xia, Xianliang Yang, Zichuan Liu, Zhihao Liu, Lei Song, Jiang Bian
2024 International Conference on Machine Learning | June 2024
Stock Trend Prediction with Multi-granularity Data: A Contrastive Learning Approach with Adaptive Fusion
Min Hou, Chang Xu, Zhi Li, Yang Liu, Weiqing Liu, Enhong Chen, Jiang Bian
CIKM 221 | April 2021
DeepGBM: A Deep Learning Framework Distilled by GBDT for Online Prediction Tasks
Guolin Ke, Zhenhui Xu, Jia Zhang, Jiang Bian, Tie-Yan Liu
KDD '19 Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining | August 2019
-
NaturalSpeech 3: Zero-Shot Speech Synthesis with Factorized Codec and Diffusion Models
Zeqian Ju, Yuancheng Wang, Kai Shen, Xu Tan, Detai Xin, Dongchao Yang, Yanqing Liu, Yichong Leng, Kaitao Song, Siliang Tang, Zhizheng Wu, Tao Qin, Xiang-Yang Li, Wei Ye, Shikun Zhang, Jiang Bian, Lei He, Jinyu Li, Sheng Zhao
ICML | June 2024
MuseCoco: Generating Symbolic Music from Text
Peiling Lu, Xin Xu, Chenfei Kang, Botao Yu, Chengyi Xing, Xu Tan, Jiang Bian
June 2023
-
RD2Bench: Toward Data-Centric Automatic R&D
Haotian Chen, Xinjie Shen, Zeqi Ye, Xiao Yang, Xu Yang, Weiqing Liu, Jiang Bian
April 2024
Leveraging Large Language Model for Automatic Evolving of Industrial Data-Centric R&D Cycle
Xu Yang, Xiao Yang, Weiqing Liu, Jinhui Li, Peng Yu, Zeqi Ye, Jiang Bian
October 2023
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PromptTTS 2: Describing and Generating Voices with Text Prompt
Yichong Leng, Zhifang Guo, Kai Shen, Xu Tan, Zeqian Ju, Yanqing Liu, Yufei Liu, Dongchao Yang, Leying Zhang, Kaitao Song, Lei He, Xiang-Yang Li, Sheng Zhao, Tao Qin, Jiang Bian
ICLR 2024 | September 2023
NaturalSpeech 2: Latent Diffusion Models are Natural and Zero-Shot Speech and Singing Synthesizers
Kai Shen, Zeqian Ju, Xu Tan, Yanqing Liu, Yichong Leng, Lei He, Tao Qin, Sheng Zhao, Jiang Bian
ICLR 2024 | April 2023
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Near-real-time monitoring of global ocean carbon sink
Piyu Ke, Xiaofan Gui, Wei Cao, Dezhi Wang, Ce Hou, Lixing Wang, Xuanren Song, Yun Li, Biqing Zhu, Jiang Bian, Stephen Sitch, Philippe Ciais, Pierre Friedlingstein, Zhu Liu
December 2023
Mimicking atmospheric photochemical modeling with a deep neural network
Jia Xing, Shuxin Zheng, Siwei Li, Lin Huang, Xiaochun Wang, James T Kelly, Shuxiao Wang, Chang Liu, Carey J. Jang, Yun Zhu, Jia Zhang, Jiang Bian, Tie-Yan Liu, Jiming Hao
Atmospheric Research | December 2021, Vol 265: pp. 105919
Exploring deep learning for air pollutant emission estimation
Lin Huang, Song Liu, Zeyuan Yang, Jia Xing, Jia Zhang, Jiang Bian, Siwei Li, Shovan Kumar Sahu, Shuxiao Wang, Tie-Yan Liu
Geoscientific Model Development | July 2021, Vol 14(7): pp. 4641-4654
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On the Generalization Properties of Diffusion Models
Puheng Li, Zhong Li, Huishuai Zhang, Jiang Bian
2023 Neural Information Processing Systems | September 2023
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Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping
Jiyan He, Xuechen Li, Da Yu, Huishuai Zhang, Janardhan (Jana) Kulkarni, Yin Tat Lee, Arturs Backurs, Nenghai Yu, Jiang Bian
International Conference on Learning Representations (ICLR) 2023 | May 2023
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Learning Differential Operators for Interpretable Time Series Modeling
Yingtao Luo, Chang Xu, Yang Liu, Weiqing Liu, Shun Zheng, Jiang Bian
KDD 2022 | August 2022
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Multi-Granularity Residual Learning with Confidence Estimation for Time Series Prediction
Min Hou, Chang Xu, Zhi Li, Yang Liu, Weiqing Liu, Enhong Chen, Jiang Bian
WWW 2022 | April 2022
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Learning Physics-Informed Neural Networks without Stacked Back-propagation
Di He, Wenlei Shi, Shanda Li, Xiaotian Gao, Jia Zhang, Jiang Bian, Liwei Wang, Tie-Yan Liu
AISTATS 2023 | April 2023
Publications by Type
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IGOR: Image-GOal Representations are the Atomic Control Units for Foundation Models in Embodied AI
Xiaoyu Chen, Junliang Guo, Tianyu He, Chuheng Zhang, Pushi Zhang, Derek Yang, Li Zhao, Jiang Bian
October 2024
Compositional 3D-aware Video Generation with LLM Director
Hanxin Zhu, Tianyu He, Anni Tang, Junliang Guo, Zhibo Chen, Jiang Bian
NeurIPS 2024 | August 2024
Diversification of Adaptive Policy for Effective Offline Reinforcement Learning
Yunseon Choi, Li Zhao, Chuheng Zhang, Lei Song, Jiang Bian, Kee-Eung Kim
IJCAI 2024 | July 2024
ProbTS: Benchmarking Point and Distributional Forecasting across Diverse Prediction Horizons
Jiawen Zhang, Xumeng Wen, Zhenwei Zhang, Shun Zheng, Jia Li, Jiang Bian
NeurIPS 2024 | June 2024
Position: Rethinking Post-Hoc Search-Based Neural Approaches for Solving Large-Scale Traveling Salesman Problems
Yifan Xia, Xianliang Yang, Zichuan Liu, Zhihao Liu, Lei Song, Jiang Bian
2024 International Conference on Machine Learning | June 2024
NaturalSpeech 3: Zero-Shot Speech Synthesis with Factorized Codec and Diffusion Models
Zeqian Ju, Yuancheng Wang, Kai Shen, Xu Tan, Detai Xin, Dongchao Yang, Yanqing Liu, Yichong Leng, Kaitao Song, Siliang Tang, Zhizheng Wu, Tao Qin, Xiang-Yang Li, Wei Ye, Shikun Zhang, Jiang Bian, Lei He, Jinyu Li, Sheng Zhao
ICML | June 2024
Whittle Index with Multiple Actions and State Constraint for Inventory Management
Chuheng Zhang, Xiangsen Wang, Wei Jiang, Xianliang Yang, Siwei Wang, Lei Song, Jiang Bian
2024 International Conference on Learning Representations | May 2024
GAIA: Zero-shot Talking Avatar Generation
Tianyu He, Junliang Guo, Runyi Yu, Yuchi Wang, Jialiang Zhu, Kaikai An, Leyi Li, Xu Tan, Chunyu Wang, HsiangTao Wu, Sheng Zhao, Jiang Bian
2024 International Conference on Learning Representations | May 2024
Protecting Your LLMs with Information Bottleneck
Zichuan Liu, Zefan Wang, Linjie Xu, Jinyu Wang, Lei Song, Tianchun Wang, Chunlin Chen, Wei Cheng, Jiang Bian
NeurIPS 2024 | April 2024
MG-TSD: Multi-Granularity Time Series Diffusion Models with Guided Learning Process
Xinyao Fan, Yueying Wu, Chang Xu, Yuhao Huang, Weiqing Liu, Jiang Bian
ICLR 2024 | March 2024
AUDIT: Audio Editing by Following Instructions with Latent Diffusion Models
Yuancheng Wang, Zeqian Ju, Xu Tan, Lei He, Zhizheng Wu, Jiang Bian, Sheng Zhao
NeurIPS 2023 | December 2023
Distributional Pareto-Optimal Multi-Objective Reinforcement Learning
Xinqiang Cai, Pushi Zhang, Li Zhao, Jiang Bian, Masashi Sugiyama, Ashley J. Llorens
2023 Neural Information Processing Systems | December 2023
BatteryML: An Open-source platform for Machine Learning on Battery Degradation
Han Zhang, Xiaofan Gui, Shun Zheng, Ziheng Lu, Yuqi Li, Jiang Bian
ICLR 2024 | October 2023
DAE-Talker: High Fidelity Speech-Driven Talking Face Generation with Diffusion Autoencoder
Tianyu He, Sheng Zhao, Jiang Bian
ACM International Conference on Multimedia | October 2023
HiFace: High-Fidelity 3D Face Reconstruction by Learning Static and Dynamic Details
Tianyu He, Muscle Wu, Sheng Zhao, Jiang Bian
2023 International Conference on Computer Vision | October 2023
UniAudio: An Audio Foundation Model Toward Universal Audio Generation
Dongchao Yang, Jinchuan Tian, Xu Tan, Rongjie Huang, Songxiang Liu, Xuankai Chang, Jiatong Shi, Sheng Zhao, Jiang Bian, Xixin Wu, Zhou Zhao, Helen Meng
ICML 2024 | September 2023
On the Generalization Properties of Diffusion Models
Puheng Li, Zhong Li, Huishuai Zhang, Jiang Bian
2023 Neural Information Processing Systems | September 2023
Connecting Large Language Models with Evolutionary Algorithms Yields Powerful Prompt Optimizers
Qingyan Guo, Rui Wang, Junliang Guo, Bei Li, Kaitao Song, Xu Tan, Guoqing Liu, Jiang Bian, Yuqing Yang
ICLR 2024 | September 2023
PromptTTS 2: Describing and Generating Voices with Text Prompt
Yichong Leng, Zhifang Guo, Kai Shen, Xu Tan, Zeqian Ju, Yanqing Liu, Yufei Liu, Dongchao Yang, Leying Zhang, Kaitao Song, Lei He, Xiang-Yang Li, Sheng Zhao, Tao Qin, Jiang Bian
ICLR 2024 | September 2023
Learning Pareto-Optimal Policies for Multi-Objective Joint Distribution
Xin-Qiang Cai, Pushi Zhang, Li Zhao, Jiang Bian, Masashi Sugiyama, Ashley J. Llorens
NeurIPS 2023 | September 2023
Robust Situational Reinforcement Learning in Face of Context Disturbances
Jinpeng Zhang, Yufeng Zheng, Chuheng Zhang, Li Zhao, Lei Song, Yuan Zhou, Jiang Bian
Proceedings of the 40th International Conference on Machine Learning (ICML) | September 2023
Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping
Jiyan He, Xuechen Li, Da Yu, Huishuai Zhang, Janardhan (Jana) Kulkarni, Yin Tat Lee, Arturs Backurs, Nenghai Yu, Jiang Bian
International Conference on Learning Representations (ICLR) 2023 | May 2023
Learning Physics-Informed Neural Networks without Stacked Back-propagation
Di He, Wenlei Shi, Shanda Li, Xiaotian Gao, Jia Zhang, Jiang Bian, Liwei Wang, Tie-Yan Liu
AISTATS 2023 | April 2023
NaturalSpeech 2: Latent Diffusion Models are Natural and Zero-Shot Speech and Singing Synthesizers
Kai Shen, Zeqian Ju, Xu Tan, Yanqing Liu, Yichong Leng, Lei He, Tao Qin, Sheng Zhao, Jiang Bian
ICLR 2024 | April 2023
Pointerformer: Deep Reinforced Multi-Pointer Transformer for the Traveling Salesman Problem
Yan Jin, Yuandong Ding, Xuanhao Pan, Kun He, Li Zhao, Tao Qin, Lei Song, Jiang Bian
AAAI 2023 | February 2023
TD3 with Reverse KL Regularizer for Offline Reinforcement Learning from Mixed Datasets
Yuanying Cai, Chuheng Zhang, Li Zhao, Wei Shen, Xuyun Zhang, Lei Song, Jiang Bian, Tao Qin, Tie-Yan Liu
IEEE International Conference on Data Mining (Best Student Paper Runner-Up Awards) | January 2023
Efficient and Effective Multi-task Grouping via Meta Learning on Task Combinations
Xiaozhuang Song, Shun Zheng, Wei Cao, James Yu, Jiang Bian
2022 Neural Information Processing Systems | November 2022
Learning Differential Operators for Interpretable Time Series Modeling
Yingtao Luo, Chang Xu, Yang Liu, Weiqing Liu, Shun Zheng, Jiang Bian
KDD 2022 | August 2022
Towards Applicable Reinforcement Learning: Improving the Generalization and Sample Efficiency with Policy Ensemble
Zhengyu Yang, Kan Ren, Xufang Luo, Minghuan Liu, Weiqing Liu, Jiang Bian, Weinan Zhang, Dongsheng Li
IJCAI 2022 | July 2022
Multi-Granularity Residual Learning with Confidence Estimation for Time Series Prediction
Min Hou, Chang Xu, Zhi Li, Yang Liu, Weiqing Liu, Enhong Chen, Jiang Bian
WWW 2022 | April 2022
DEPTS: Deep Expansion Learning for Periodic Time Series Forecasting
Wei Fan, Shun Zheng, Xiaohan Yi, Wei Cao, Yanjie Fu, Jiang Bian, Tie-Yan Liu
ICLR 2022 | April 2022
DDG-DA: Data Distribution Generation for Predictable Concept Drift Adaptation
Wendi Li, Xiao Yang, Weiqing Liu, Yingce Xia, Jiang Bian
AAAI 2022 | January 2022
Deep Risk Model: A Deep Learning Solution for Mining Latent Risk Factors to Improve Covariance Matrix Estimation
Hengxu Lin, Dong Zhou, Weiqing Liu, Jiang Bian
ICAIF 2021 | November 2021
Learning Multiple Stock Trading Patterns with Temporal Routing Adaptor and Optimal Transport
Hengxu Lin, Dong Zhou, Weiqing Liu, Jiang Bian
KDD 2021 | August 2021
Stock Trend Prediction with Multi-granularity Data: A Contrastive Learning Approach with Adaptive Fusion
Min Hou, Chang Xu, Zhi Li, Yang Liu, Weiqing Liu, Enhong Chen, Jiang Bian
CIKM 221 | April 2021
REST: Relational Event-driven Stock Trend Forecasting
Wentao Xu, Weiqing Liu, Chang Xu, Jiang Bian, Jian Yin, Tie-Yan Liu
2021 The Web Conference | April 2021
Universal Trading for Order Execution with Oracle Policy Distillation
Yuchen Fang, Kan Ren, Weiqing Liu, Dong Zhou, Weinan Zhang, Jiang Bian, Yong Yu, Tie-Yan Liu
AAAI | February 2021
Cooperative Policy Learning with Pre-trained Heterogeneous Observation Representations
Wenlei Shi, Xinran Wei, Jia Zhang, Xiaoyuan Ni, Arthur Jiang, Jiang Bian, Tie-Yan Liu
AAMAS 2021 | December 2020
Invertible Image Rescaling
Mingqing Xiao, Shuxin Zheng, Chang Liu, Yaolong Wang, Di He, Guolin Ke, Jiang Bian, Zhouchen Lin, Tie-Yan Liu
16th European Conference Computer Vision (ECCV 2020) | August 2020
Conservative or Aggressive? Confidence-Aware Dynamic Portfolio Construction
Lewen Wang, Weiqing Liu, Xiao Yang, Jiang Bian
2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP) | November 2019
A Divide-and-Conquer Framework for Attention-based Combination of Multiple Investment Strategies
Xiao Yang, Weiqing Liu, Lewen Wang, Cheng Qu, Jiang Bian
2019 IEEE Global Conference on Signal and Information Processing (GlobalSIP) | November 2019
Individualized Indicator for All: Stock-wise Technical Indicator Optimization with Stock Embedding
Zhige Li, Derek Yang, Li Zhao, Jiang Bian, Tao Qin, Tie-Yan Liu
25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining | August 2019
Investment Behaviors Can Tell What Inside: Exploring Stock Intrinsic Properties for Stock Trend Prediction
Chi Chen, Li Zhao, Jiang Bian, Chunxiao Xing, Tie-Yan Liu
25th ACM SIGKDD Conference on Knowledge Discover and Data Mining(KDD 2019) | August 2019
DeepGBM: A Deep Learning Framework Distilled by GBDT for Online Prediction Tasks
Guolin Ke, Zhenhui Xu, Jia Zhang, Jiang Bian, Tie-Yan Liu
KDD '19 Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining | August 2019
A Cooperative Multi-Agent Reinforcement Learning Framework for Resource Balancing in Complex Logistics Network
Xihan Li, Jia Zhang, Jiang Bian, Yunhai Tong, Tie-Yan Liu
AAMAS 2019 | March 2019
Trust Region Evolution Strategies
Guoqing Liu, Li Zhao, Feidiao Yang, Jiang Bian, Tao Qin, Nenghai Yu, Tie-Yan Liu
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence | February 2019
Investor-Imitator: A Framework for Trading Knowledge Extraction
Yi Ding, Weiqing Liu, Jiang Bian, Daoqiang Zhang, Tie-Yan Liu
Knowledge Discovery & Data Mining | July 2018
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ElasTST: Towards Robust Varied-Horizon Forecasting with Elastic Time-Series Transformer
Shun Zheng, Xumeng Wen, Jiang Bian
October 2024
BPQP: A Differentiable Convex Optimization Framework for Efficient End-to-End Learning
Xiao Yang, Xu Yang, Weiqing Liu, Lewen Wang, Jiang Bian
October 2024
Near-real-time monitoring of global ocean carbon sink
Piyu Ke, Xiaofan Gui, Wei Cao, Dezhi Wang, Ce Hou, Lixing Wang, Xuanren Song, Yun Li, Biqing Zhu, Jiang Bian, Stephen Sitch, Philippe Ciais, Pierre Friedlingstein, Zhu Liu
December 2023
MuseCoco: Generating Symbolic Music from Text
Peiling Lu, Xin Xu, Chenfei Kang, Botao Yu, Chengyi Xing, Xu Tan, Jiang Bian
June 2023
Demonstration Actor Critic
Guoqing Liu, Li Zhao, Pushi Zhang, Jiang Bian, Tao Qin, Nenghai Yu, Tie-Yan Liu
November 2019
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LordNet: An efficient neural network for learning to solve parametric partial differential equations without simulated data
Xinquan Huang, Wenlei Shi, Xiaotian Gao, Xinran wei, Jia Zhang, Jiang Bian, Mao Yang, Tie-Yan Liu
Neural Networks | August 2024
NuTime: Numerically Multi-Scaled Embedding for Large-Scale Time Series Pretraining
Chenguo Lin, Xumeng Wen, Wei Cao, Congrui Huang, Jiang Bian, Stephen Lin, Zhirong Wu
Transactions on Machine Learning Research | July 2024
Memories are One-to-Many Mapping Alleviators in Talking Face Generation
Tianyu He, Sheng Zhao, Jiang Bian
IEEE Transactions on Pattern Analysis and Machine Intelligence | June 2024
Pre-Trained Large Language Models for Industrial Control
Lei Song, Chuheng Zhang, Li Zhao, Jiang Bian
ArXiv | August 2023, Vol abs/2308.03028
Mimicking atmospheric photochemical modeling with a deep neural network
Jia Xing, Shuxin Zheng, Siwei Li, Lin Huang, Xiaochun Wang, James T Kelly, Shuxiao Wang, Chang Liu, Carey J. Jang, Yun Zhu, Jia Zhang, Jiang Bian, Tie-Yan Liu, Jiming Hao
Atmospheric Research | December 2021, Vol 265: pp. 105919
Exploring deep learning for air pollutant emission estimation
Lin Huang, Song Liu, Zeyuan Yang, Jia Xing, Jia Zhang, Jiang Bian, Siwei Li, Shovan Kumar Sahu, Shuxiao Wang, Tie-Yan Liu
Geoscientific Model Development | July 2021, Vol 14(7): pp. 4641-4654
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Video In-context Learning
Wentao Zhang, Junliang Guo, Tianyu He, Li Zhao, Linli Xu, Jiang Bian
July 2024
RD2Bench: Toward Data-Centric Automatic R&D
Haotian Chen, Xinjie Shen, Zeqi Ye, Xiao Yang, Xu Yang, Weiqing Liu, Jiang Bian
April 2024
Leveraging Large Language Model for Automatic Evolving of Industrial Data-Centric R&D Cycle
Xu Yang, Xiao Yang, Weiqing Liu, Jinhui Li, Peng Yu, Zeqi Ye, Jiang Bian
October 2023
Towards Foundation Models for Learning on Tabular Data
Han Zhang, Xumeng Wen, Shun Zheng, Wei Xu, Jiang Bian
October 2023
ADD: Augmented Disentanglement Distillation Framework for Improving Stock Trend Forecasting
Hongshun Tang, Lijun Wu, Weiqing Liu, Jiang Bian
December 2021
Trimming the Sail: A Second-order Learning Paradigm for Stock Prediction
Chi Chen, Li Zhao, Wei Cao, Jiang Bian, Chunxiao Xing
February 2020