Chin-Wei Huang

Publications

AR-DAE: Towards Unbiased Neural Entropy Gradient Estimation. Jae Hyun Lim, Aaron Courville, Christopher Pal, Chin-Wei Huang. At International Conference on Machine Learning (ICML), 2020.

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Stochastic Neural Network with Kronecker Flow. Chin-Wei Huang, Ahmed Touati, Pascal Vincent, Gintare Karolina Dziugaite, Alexandre Lacoste, Aaron Courville. At International Conference on Artificial Intelligence and Statistics (AISTATS), 2020.

Hierarchical Importance Weighted Autoencoders. Chin-Wei Huang, Kris Sankaran, Eeshan Dhekane, Alexandre Lacoste, Aaron Courville. At International Conference on Machine Learning (ICML), 2019.

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Stochastic Neural Network with Kronecker Flow. Chin-Wei Huang, Ahmed Touati, Pascal Vincent, Gintare Karolina Dziugaite, Alexandre Lacoste, Aaron Courville. At Workshop at the International Conference on Machine Learning (ICML), 2019.

On Difficulties of Probability Distillation. Chin-Wei Huang, Faruk Ahmed, Kundan Kumar, Alexandre Lacoste, Aaron Courville. At International Conference on Learning Representations (ICLR), 2019.

Improving Explorability in Variational Inference with Annealed Variational Objectives. Chin-Wei Huang, Shawn Tan, Alexandre Lacoste, Aaron Courville. At Conference on Neural Information Processing Systems (NeurIPS), 2018.

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Neural Autoregressive Flows. Chin-Wei Huang, David Krueger, Alexandre Lacoste, Aaron Courville. At International Conference on Machine Learning (ICML), 2018.

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Bayesian Hypernetworks. David Krueger, Chin-Wei Huang, Riashat Islam, Ryan Turner, Alexandre Lacoste, Aaron Courville. At Workshop at the Neural Information Processing Systems (NeurIPS), 2017.