167 citations · 188 across the 11 of their papers we have counts for
23 papers
On the Design Space of Discrete Diffusion Online Adaptation for Molecular Optimization
Trevor Chen, Ariel Dai, Jason Yang +8
Molecular optimization often starts from a pretrained generative model that captures a broad prior over valid molecular structures. At test time, however, the goal is not to sample…
Few-step Cofolding with All-Atom Flow Maps
Gianluca Scarpellini, Ron Shprints, Peter Holderrieth +7
All-atom generative modeling of 3D biomolecular complexes has emerged as the dominant paradigm for predicting the structure of proteins and protein-ligand systems. Generating struc…
Pearl: A Foundation Model for Placing Every Atom in the Right Location
Genesis Research Team, Alejandro Dobles, Nina Jovic +37
Accurately predicting the three-dimensional structures of protein-ligand complexes remains a fundamental challenge in computational drug discovery that limits the pace and success…
Triangle Multiplication Is All You Need For Biomolecular Structure Representations
Jeffrey Ouyang-Zhang, Pranav Murugan, Daniel J. Diaz +7
AlphaFold has transformed protein structure prediction, but emerging applications such as virtual ligand screening, proteome-wide folding, and de novo binder design demand predicti…
Knowledge-Aware Meta-learning for Low-Resource Text Classification
Huaxiu Yao, Yingxin Wu, Maruan Al-Shedivat +1
Meta-learning has achieved great success in leveraging the historical learned knowledge to facilitate the learning process of the new task. However, merely learning the knowledge f…
A Field Guide to Federated Optimization
Jianyu Wang, Zachary Charles, Zheng Xu +50
Federated learning and analytics are a distributed approach for collaboratively learning models (or statistics) from decentralized data, motivated by and designed for privacy prote…