1 citations · 2 across the 7 of their papers we have counts for
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Stochastic Control Policies for Robust Molecular Transition Path Sampling
Jingqian Liu, Yu-Hsiang Wang, Yanru Qu +1
Transition path sampling (TPS) aims to efficiently generate rare molecular transition trajectories between metastable states and is essential for understanding biomolecular mechani…
Variable-Length Generative Protein Design via Generalized Poisson Flow
Chaoran Cheng, Zhanghan Ni, Yanru Qu +4
The ability to generate variable-length proteins is crucial in protein design, where the optimal length is often unknown and tightly coupled to designability. Current diffusion- an…
Protein Autoregressive Modeling via Multiscale Structure Generation
Yanru Qu, Cheng-Yen Hsieh, Zaixiang Zheng +2
We present protein autoregressive modeling (PAR), the first multi-scale autoregressive framework for protein backbone generation via coarse-to-fine next-scale prediction. Using the…
Riemannian Consistency Model
Chaoran Cheng, Yusong Wang, Yuxin Chen +3
Consistency models are a class of generative models that enable few-step generation for diffusion and flow matching models. While consistency models have achieved promising results…
Flow Matching Meets Biology and Life Science: A Survey
Zihao Li, Zhichen Zeng, Xiao Lin +9
Over the past decade, advances in generative modeling, such as generative adversarial networks, masked autoencoders, and diffusion models, have significantly transformed biological…
-Flow: A Unified Framework for Continuous-State Discrete Flow Matching Models
Chaoran Cheng, Jiahan Li, Jiajun Fan +1
Recent efforts have extended the flow-matching framework to discrete generative modeling. One strand of models directly works with the continuous probabilities instead of discrete…