Brief Report: Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks
Yikeng Shen, Shawn Tan, Alessandro Sordoni, Aaron Courville
ICLR 2019 | May 2019
ICLR 2019 Best Paper Award
论文与出版物
论文与出版物
按年份分类的论文与出版物
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Deep Graph Infomax
Petar Veličković, William Fedus, William L. Hamilton, Pietro Liò, Yoshua Bengio, Devon Hjelm
ICLR 2019 | May 2019
G-SGD: Optimizing ReLU Neural Networks in its Positively Scale-Invariant Space
Qi Meng, Shuxin Zheng, Huishuai Zhang, Wei Chen, Qiwei Ye, Zhi-Ming Ma, Nenghai Yu, Tie-Yan Liu
International Conference on Learning Representations | May 2019
Learning to Represent Edits
Pengcheng Yin, Graham Neubig, Miltiadis Allamanis, Marc Brockschmidt, Alexander Gaunt
ICLR 2019 | May 2019
arXiv:1810.13337 [cs.LG]
Neural TTS Stylization with Adversarial and Collaborative Games
ShuangMa, Daniel McDuff, Yale Song
International Conference on Learning Representations (ICLR) | April 2019
Visceral Machines: Risk-Aversion in Reinforcement Learning with Intrinsic Physiological Rewards
Daniel McDuff, Ashish Kapoor
ICLR 2019 | April 2019
Learning deep representations by mutual information estimation and maximization
Devon Hjelm, Alex Fedorov, Samuel Lavoie-Marchildon, Karan Grewal, Philip Bachman, Adam Trischler, Yoshua Bengio
ICLR 2019 | April 2019
-
Label super-resolution networks
Kolya Malkin, Caleb Robinson, Le Hou, Rachel Soobitsky, Jacob Czawlytko, Dimitris Samaras, Joel H. Saltz, Lucas Joppa, Nebojsa Jojic
ICLR 2019 | September 2018
按研究领域分类的论文与出版物
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Brief Report: Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks
Yikeng Shen, Shawn Tan, Alessandro Sordoni, Aaron Courville
ICLR 2019 | May 2019
ICLR 2019 Best Paper Award
Deep Graph Infomax
Petar Veličković, William Fedus, William L. Hamilton, Pietro Liò, Yoshua Bengio, Devon Hjelm
ICLR 2019 | May 2019
Learning to Represent Edits
Pengcheng Yin, Graham Neubig, Miltiadis Allamanis, Marc Brockschmidt, Alexander Gaunt
ICLR 2019 | May 2019
arXiv:1810.13337 [cs.LG]
G-SGD: Optimizing ReLU Neural Networks in its Positively Scale-Invariant Space
Qi Meng, Shuxin Zheng, Huishuai Zhang, Wei Chen, Qiwei Ye, Zhi-Ming Ma, Nenghai Yu, Tie-Yan Liu
International Conference on Learning Representations | May 2019
Neural TTS Stylization with Adversarial and Collaborative Games
ShuangMa, Daniel McDuff, Yale Song
International Conference on Learning Representations (ICLR) | April 2019
Visceral Machines: Risk-Aversion in Reinforcement Learning with Intrinsic Physiological Rewards
Daniel McDuff, Ashish Kapoor
ICLR 2019 | April 2019
Learning deep representations by mutual information estimation and maximization
Devon Hjelm, Alex Fedorov, Samuel Lavoie-Marchildon, Karan Grewal, Philip Bachman, Adam Trischler, Yoshua Bengio
ICLR 2019 | April 2019
Label super-resolution networks
Kolya Malkin, Caleb Robinson, Le Hou, Rachel Soobitsky, Jacob Czawlytko, Dimitris Samaras, Joel H. Saltz, Lucas Joppa, Nebojsa Jojic
ICLR 2019 | September 2018
-
Label super-resolution networks
Kolya Malkin, Caleb Robinson, Le Hou, Rachel Soobitsky, Jacob Czawlytko, Dimitris Samaras, Joel H. Saltz, Lucas Joppa, Nebojsa Jojic
ICLR 2019 | September 2018
-
Label super-resolution networks
Kolya Malkin, Caleb Robinson, Le Hou, Rachel Soobitsky, Jacob Czawlytko, Dimitris Samaras, Joel H. Saltz, Lucas Joppa, Nebojsa Jojic
ICLR 2019 | September 2018
-
Learning to Represent Edits
Pengcheng Yin, Graham Neubig, Miltiadis Allamanis, Marc Brockschmidt, Alexander Gaunt
ICLR 2019 | May 2019
arXiv:1810.13337 [cs.LG]
-
G-SGD: Optimizing ReLU Neural Networks in its Positively Scale-Invariant Space
Qi Meng, Shuxin Zheng, Huishuai Zhang, Wei Chen, Qiwei Ye, Zhi-Ming Ma, Nenghai Yu, Tie-Yan Liu
International Conference on Learning Representations | May 2019
按类型分类的论文与出版物
-
Brief Report: Ordered Neurons: Integrating Tree Structures into Recurrent Neural Networks
Yikeng Shen, Shawn Tan, Alessandro Sordoni, Aaron Courville
ICLR 2019 | May 2019
ICLR 2019 Best Paper Award
Deep Graph Infomax
Petar Veličković, William Fedus, William L. Hamilton, Pietro Liò, Yoshua Bengio, Devon Hjelm
ICLR 2019 | May 2019
Learning to Represent Edits
Pengcheng Yin, Graham Neubig, Miltiadis Allamanis, Marc Brockschmidt, Alexander Gaunt
ICLR 2019 | May 2019
arXiv:1810.13337 [cs.LG]
G-SGD: Optimizing ReLU Neural Networks in its Positively Scale-Invariant Space
Qi Meng, Shuxin Zheng, Huishuai Zhang, Wei Chen, Qiwei Ye, Zhi-Ming Ma, Nenghai Yu, Tie-Yan Liu
International Conference on Learning Representations | May 2019
Neural TTS Stylization with Adversarial and Collaborative Games
ShuangMa, Daniel McDuff, Yale Song
International Conference on Learning Representations (ICLR) | April 2019
Visceral Machines: Risk-Aversion in Reinforcement Learning with Intrinsic Physiological Rewards
Daniel McDuff, Ashish Kapoor
ICLR 2019 | April 2019
Learning deep representations by mutual information estimation and maximization
Devon Hjelm, Alex Fedorov, Samuel Lavoie-Marchildon, Karan Grewal, Philip Bachman, Adam Trischler, Yoshua Bengio
ICLR 2019 | April 2019
Label super-resolution networks
Kolya Malkin, Caleb Robinson, Le Hou, Rachel Soobitsky, Jacob Czawlytko, Dimitris Samaras, Joel H. Saltz, Lucas Joppa, Nebojsa Jojic
ICLR 2019 | September 2018