| Variational autoencoders with jointly optimized latent dependency structure J He, Y Gong, J Marino, G Mori, A Lehrmann International Conference on Learning Representations, 2019 | 11 | 2019 |
| Variational selective autoencoder Y Gong, H Hajimirsadeghi, J He, M Nawhal, T Durand, G Mori Second Symposium on Advances in Approximate Bayesian Inference, 2020 | 7 | 2020 |
| Variational selective autoencoder: Learning from partially-observed heterogeneous data Y Gong, H Hajimirsadeghi, J He, T Durand, G Mori International Conference on Artificial Intelligence and Statistics, 2377-2385, 2021 | 5 | 2021 |
| RankSim: Ranking Similarity Regularization for Deep Imbalanced Regression Y Gong, G Mori, F Tung International Conference on Machine Learning 162, 7634-7649, 2022 | 2 | 2022 |
| Muse: Feature self-distillation with mutual information and self-information Y Gong, Y Yu, G Mittal, G Mori, M Chen arXiv preprint arXiv:2110.12606, 2021 | 2 | 2021 |
| System and method for machine learning architecture for partially-observed multimodal data Y Gong, J He, T Durand, M Nawhal, CAO Yanshuai, M Gregory, ... US Patent App. 16/882,074, 2020 | 2 | 2020 |
| Latent structure learning in variational autoencoders Y Gong Simon Fraser University, 2019 | | 2019 |
| Learning from Partially-Observed Multimodal Data with Variational Autoencoders Y Gong, H Hajimirsadeghi, J He, M Nawhal, T Durand, G Mori | | |
| Variational Latent Dependency Learning J He, Y Gong, J Marino, G Mori, A Lehrmann | | |
