52 citations · 107 across the 10 of their papers we have counts for
5 papers · 1 filter
Continuously Tempered Diffusion Samplers
Ezra Erives, Bowen Jing, Peter Holderrieth +1
Annealing-based neural samplers seek to amortize sampling from unnormalized distributions by training neural networks to transport a family of densities interpolating from source t…
Verlet Flows: Exact-Likelihood Integrators for Flow-Based Generative Models
Ezra Erives, Bowen Jing, Tommi Jaakkola
Approximations in computing model likelihoods with continuous normalizing flows (CNFs) hinder the use of these models for importance sampling of Boltzmann distributions, where exac…
Harmonic Self-Conditioned Flow Matching for Multi-Ligand Docking and Binding Site Design
Hannes Stärk, Bowen Jing, Regina Barzilay +1
A significant amount of protein function requires binding small molecules, including enzymatic catalysis. As such, designing binding pockets for small molecules has several impactf…
Equivariant Graph Neural Networks for 3D Macromolecular Structure
Bowen Jing, Stephan Eismann, Pratham N. Soni +1
Representing and reasoning about 3D structures of macromolecules is emerging as a distinct challenge in machine learning. Here, we extend recent work on geometric vector perceptron…
SGVAE: Sequential Graph Variational Autoencoder
Bowen Jing, Ethan A. Chi, Jillian Tang
Generative models of graphs are well-known, but many existing models are limited in scalability and expressivity. We present a novel sequential graphical variational autoencoder op…