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Two for One: Diffusion Models and Force Fields for Coarse-Grained Molecular Dynamics


Feb 01, 2023
Marloes Arts, Victor Garcia Satorras, Chin-Wei Huang, Daniel Zuegner, Marco Federici, Cecilia Clementi, Frank Noé, Robert Pinsler, Rianne van den Berg

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Waveform Design for Optimal PSL Under Spectral and Unimodular Constraints via Alternating Minimization


Oct 16, 2022
Chin-Wei Huang, Li-Fu Chen, Borching Su

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* 11 pages, 5 figures. This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessible 

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Riemannian Diffusion Models


Aug 16, 2022
Chin-Wei Huang, Milad Aghajohari, Avishek Joey Bose, Prakash Panangaden, Aaron Courville

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A Variational Perspective on Diffusion-Based Generative Models and Score Matching


Jun 05, 2021
Chin-Wei Huang, Jae Hyun Lim, Aaron Courville

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Convex Potential Flows: Universal Probability Distributions with Optimal Transport and Convex Optimization


Dec 10, 2020
Chin-Wei Huang, Ricky T. Q. Chen, Christos Tsirigotis, Aaron Courville

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RealCause: Realistic Causal Inference Benchmarking


Nov 30, 2020
Brady Neal, Chin-Wei Huang, Sunand Raghupathi

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* Working paper 

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AR-DAE: Towards Unbiased Neural Entropy Gradient Estimation


Jun 09, 2020
Jae Hyun Lim, Aaron Courville, Christopher Pal, Chin-Wei Huang

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* accepted in ICML 2020 

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Augmented Normalizing Flows: Bridging the Gap Between Generative Flows and Latent Variable Models


Feb 17, 2020
Chin-Wei Huang, Laurent Dinh, Aaron Courville

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* 27 pages, 12 figures 

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vGraph: A Generative Model for Joint Community Detection and Node Representation Learning


Jun 18, 2019
Fan-Yun Sun, Meng Qu, Jordan Hoffmann, Chin-Wei Huang, Jian Tang

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* In submission 

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Stochastic Neural Network with Kronecker Flow


Jun 10, 2019
Chin-Wei Huang, Ahmed Touati, Pascal Vincent, Gintare Karolina Dziugaite, Alexandre Lacoste, Aaron Courville

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* 18 pages 

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