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Ricky T. Q. Chen
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Distributional GFlowNets with Quantile Flows


Feb 11, 2023
Dinghuai Zhang, Ling Pan, Ricky T. Q. Chen, Aaron Courville, Yoshua Bengio

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Riemannian Flow Matching on General Geometries


Feb 07, 2023
Ricky T. Q. Chen, Yaron Lipman

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Latent Discretization for Continuous-time Sequence Compression


Dec 28, 2022
Ricky T. Q. Chen, Matthew Le, Matthew Muckley, Maximilian Nickel, Karen Ullrich

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Flow Matching for Generative Modeling


Oct 06, 2022
Yaron Lipman, Ricky T. Q. Chen, Heli Ben-Hamu, Maximilian Nickel, Matt Le

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Neural Conservation Laws: A Divergence-Free Perspective


Oct 04, 2022
Jack Richter-Powell, Yaron Lipman, Ricky T. Q. Chen

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* Accepted for publication at NeurIPS 2022 
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Latent State Marginalization as a Low-cost Approach for Improving Exploration


Oct 03, 2022
Dinghuai Zhang, Aaron Courville, Yoshua Bengio, Qinqing Zheng, Amy Zhang, Ricky T. Q. Chen

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Unifying Generative Models with GFlowNets


Sep 06, 2022
Dinghuai Zhang, Ricky T. Q. Chen, Nikolay Malkin, Yoshua Bengio

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* Accepted to ICML 2022 Beyond Bayes workshop 
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Matching Normalizing Flows and Probability Paths on Manifolds


Jul 11, 2022
Heli Ben-Hamu, Samuel Cohen, Joey Bose, Brandon Amos, Aditya Grover, Maximilian Nickel, Ricky T. Q. Chen, Yaron Lipman

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* ICML 2022 
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Semi-Discrete Normalizing Flows through Differentiable Tessellation


Mar 14, 2022
Ricky T. Q. Chen, Brandon Amos, Maximilian Nickel

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Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations


Feb 12, 2021
Winnie Xu, Ricky T. Q. Chen, Xuechen Li, David Duvenaud

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