Huang, Chin-Wei

14 publications

ICLR 2022 Learning to Dequantise with Truncated Flows Shawn Tan, Chin-Wei Huang, Alessandro Sordoni, Aaron Courville

NeurIPS 2022 Riemannian Diffusion Models Chin-Wei Huang, Milad Aghajohari, Joey Bose, Prakash Panangaden, Aaron C. Courville

NeurIPS 2021 A Variational Perspective on Diffusion-Based Generative Models and Score Matching Chin-Wei Huang, Jae Hyun Lim, Aaron C. Courville

ICMLW 2021 A Variational Perspective on Diffusion-Based Generative Models and Score Matching Chin-Wei Huang, Jae Hyun Lim, Aaron Courville

ICLR 2021 Convex Potential Flows: Universal Probability Distributions with Optimal Transport and Convex Optimization Chin-Wei Huang, Ricky T. Q. Chen, Christos Tsirigotis, Aaron Courville

ICML 2020 AR-DAE: Towards Unbiased Neural Entropy Gradient Estimation Jae Hyun Lim, Aaron Courville, Christopher Pal, Chin-Wei Huang

ICLRW 2020 Solving ODE with Universal Flows: Approximation Theory for Flow-Based Models Chin-Wei Huang, Laurent Dinh, Aaron Courville

AISTATS 2020 Stochastic Neural Network with Kronecker Flow Chin-Wei Huang, Ahmed Touati, Pascal Vincent, Gintare Karolina Dziugaite, Alexandre Lacoste, Aaron Courville

ICML 2019 Hierarchical Importance Weighted Autoencoders Chin-Wei Huang, Kris Sankaran, Eeshan Dhekane, Alexandre Lacoste, Aaron Courville

UAI 2019 Probability Distillation: A Caveat and Alternatives Chin-Wei Huang, Faruk Ahmed, Kundan Kumar, Alexandre Lacoste, Aaron Courville

NeurIPS 2019 vGraph: A Generative Model for Joint Community Detection and Node Representation Learning Fan-Yun Sun, Meng Qu, Jordan Hoffmann, Chin-Wei Huang, Jian Tang

NeurIPS 2018 Improving Explorability in Variational Inference with Annealed Variational Objectives Chin-Wei Huang, Shawn Tan, Alexandre Lacoste, Aaron C. Courville

ICML 2018 Neural Autoregressive Flows Chin-Wei Huang, David Krueger, Alexandre Lacoste, Aaron Courville

ICLR 2018 Neural Language Modeling by Jointly Learning Syntax and Lexicon Yikang Shen, Zhouhan Lin, Chin-wei Huang, Aaron Courville