Graphormer
Microsoft Research blog
Research at Microsoft 2023: A year of groundbreaking AI advances and discoveries
AI saw unparalleled growth in 2023, reaching millions daily. This progress owes much to the extensive work of Microsoft researchers and collaborators. In this review, learn about the advances in 2023, which set the stage for further progress in 2024.
Announcing the DeepSpeed4Science Initiative: Enabling large-scale scientific discovery through sophisticated AI system technologies
| Shuaiwen Leon Song, Bonnie Kruft, Minjia Zhang, Conglong Li, Martin Cai, and Yuxiong He
Editor’s note, Sept. 28, 2023 – The founding collaborators list was updated to correct omissions and the scientific foundation model graph was updated to correct information. In the next decade, deep learning may revolutionize the natural sciences, enhancing our capacity to…
Distributional Graphormer: Toward equilibrium distribution prediction for molecular systems
| Shuxin Zheng, Chang Liu, Yu Shi, Ziheng Lu, Fusong Ju, Jianwei Zhu, Hongxia Hao, Peiran Jin, Frank Noé, Haiguang Liu, and Tie-Yan Liu
Distributional Graphormer, Microsoft’s new deep learning framework for predicting the equilibrium distribution of molecular structures, can generate realistic and diverse molecular structures with high efficiency and low cost.
AI4Science to empower the fifth paradigm of scientific discovery
| Christopher Bishop
Editor’s note, Oct. 20, 2023 – The post was updated to remove information related to the Amsterdam lab, as those details have since changed. Over the coming decade, deep learning looks set to have a transformational impact on the natural…
People
Chang Liu
Senior Researcher
Tie-Yan Liu
Distinguished Scientist, Microsoft Research AI for Science
Yu Shi
Researcher