Chin-Wei Huang
Chin-Wei Huang
PhD Student at Mila (University of Montreal)
Verified email at umontreal.ca - Homepage
Title
Cited by
Cited by
Year
Neural autoregressive flows
CW Huang, D Krueger, A Lacoste, A Courville
arXiv preprint arXiv:1804.00779, 2018
1242018
Bayesian hypernetworks
D Krueger, CW Huang, R Islam, R Turner, A Lacoste, A Courville
arXiv preprint arXiv:1710.04759, 2017
632017
Neural language modeling by jointly learning syntax and lexicon
Y Shen, Z Lin, CW Huang, A Courville
arXiv preprint arXiv:1711.02013, 2017
602017
Improving explorability in variational inference with annealed variational objectives
CW Huang, S Tan, A Lacoste, AC Courville
Advances in Neural Information Processing Systems, 9701-9711, 2018
152018
Learnable Explicit Density for Continuous Latent Space and Variational Inference
CW Huang, A Touati, L Dinh, M Drozdzal, M Havaei, L Charlin, ...
https://arxiv.org/abs/1710.02248, 2017
122017
vGraph: A generative model for joint community detection and node representation learning
FY Sun, M Qu, J Hoffmann, CW Huang, J Tang
Advances in Neural Information Processing Systems, 514-524, 2019
62019
Augmented normalizing flows: Bridging the gap between generative flows and latent variable models
CW Huang, L Dinh, A Courville
arXiv preprint arXiv:2002.07101, 2020
52020
Hierarchical importance weighted autoencoders
CW Huang, K Sankaran, E Dhekane, A Lacoste, A Courville
arXiv preprint arXiv:1905.04866, 2019
42019
Generating contradictory, neutral, and entailing sentences
Y Shen, S Tan, CW Huang, A Courville
arXiv preprint arXiv:1803.02710, 2018
22018
Stochastic neural network with kronecker flow
CW Huang, A Touati, P Vincent, GK Dziugaite, A Lacoste, A Courville
International Conference on Artificial Intelligence and Statistics, 4184-4194, 2020
12020
Sequentialized Sampling Importance Resampling and Scalable IWAE
CW Huang, A Courville
12017
AR-DAE: Towards Unbiased Neural Entropy Gradient Estimation
JH Lim, A Courville, C Pal, CW Huang
arXiv preprint arXiv:2006.05164, 2020
2020
Solving ODE with Universal Flows: Approximation Theory for Flow-Based Models
CW Huang, L Dinh, A Courville
ICLR 2020 Workshop on Integration of Deep Neural Models and Differential …, 2020
2020
Investigating Biases in Textual Entailment Datasets
S Tan, Y Shen, C Huang, A Courville
arXiv preprint arXiv:1906.09635, 2019
2019
Note on the bias and variance of variational inference
CW Huang, A Courville
arXiv preprint arXiv:1906.03708, 2019
2019
Probability distillation: A caveat and alternatives
CW Huang, F Ahmed, K Kumar, A Lacoste, A Courville
2018
Facilitating Multimodality in Normalizing Flows
CW Huang, D Krueger, A Courville
http://bayesiandeeplearning.org/2017/papers/75.pdf, 2017
2017
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