| Neural autoregressive flows CW Huang, D Krueger, A Lacoste, A Courville arXiv preprint arXiv:1804.00779, 2018 | 124 | 2018 |
| Bayesian hypernetworks D Krueger, CW Huang, R Islam, R Turner, A Lacoste, A Courville arXiv preprint arXiv:1710.04759, 2017 | 63 | 2017 |
| Neural language modeling by jointly learning syntax and lexicon Y Shen, Z Lin, CW Huang, A Courville arXiv preprint arXiv:1711.02013, 2017 | 60 | 2017 |
| 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 | 15 | 2018 |
| 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 | 12 | 2017 |
| 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 | 6 | 2019 |
| 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 | 5 | 2020 |
| Hierarchical importance weighted autoencoders CW Huang, K Sankaran, E Dhekane, A Lacoste, A Courville arXiv preprint arXiv:1905.04866, 2019 | 4 | 2019 |
| Generating contradictory, neutral, and entailing sentences Y Shen, S Tan, CW Huang, A Courville arXiv preprint arXiv:1803.02710, 2018 | 2 | 2018 |
| 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 | 1 | 2020 |
| Sequentialized Sampling Importance Resampling and Scalable IWAE CW Huang, A Courville | 1 | 2017 |
| 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 |
Aaron CourvilleUniversité de MontréalVerified email at umontreal.ca
