activity
20232026
most citedSE(3)-Stochastic Flow Matching for Protein Backbone Generation

15 citations · 25 across the 5 of their papers we have counts for

collaborators

5 papers

q-bio.QM2026

VibeProteinBench: An Evaluation Benchmark for Language-interfaced Vibe Protein Design

Hyunjin Seo, Hongjoon Ahn, Jimin Park +16

Protein design aims to compose amino-acid sequences that fold into stable three-dimensional structures while satisfying targeted functional properties. The field is increasingly sh…

cs.LG2024★ 2 cited

Steering Masked Discrete Diffusion Models via Discrete Denoising Posterior Prediction

Jarrid Rector-Brooks, Mohsin Hasan, Zhangzhi Peng +9

Generative modeling of discrete data underlies important applications spanning text-based agents like ChatGPT to the design of the very building blocks of life in protein sequences…

cs.LG2024★ 7 cited

Sequence-Augmented SE(3)-Flow Matching For Conditional Protein Backbone Generation

Guillaume Huguet, James Vuckovic, Kilian Fatras +9

Proteins are essential for almost all biological processes and derive their diverse functions from complex 3D structures, which are in turn determined by their amino acid sequences…

cs.LG2024★ 1 cited

Iterated Denoising Energy Matching for Sampling from Boltzmann Densities

Tara Akhound-Sadegh, Jarrid Rector-Brooks, Avishek Joey Bose +9

Efficiently generating statistically independent samples from an unnormalized probability distribution, such as equilibrium samples of many-body systems, is a foundational problem…

cs.LG2023★ 15 cited

SE(3)-Stochastic Flow Matching for Protein Backbone Generation

Avishek Joey Bose, Tara Akhound-Sadegh, Guillaume Huguet +7

The computational design of novel protein structures has the potential to impact numerous scientific disciplines greatly. Toward this goal, we introduce FoldFlow, a series of novel…