| Lifelong gan: Continual learning for conditional image generation M Zhai, L Chen, F Tung, J He, M Nawhal, G Mori Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 139 | 2019 |
| Layoutvae: Stochastic scene layout generation from a label set AA Jyothi, T Durand, J He, L Sigal, G Mori Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 84 | 2019 |
| Probabilistic Video Generation using Holistic Attribute Control J He, A Lehrmann, J Marino, G Mori, L Sigal European Conference on Computer Vision, 2018 | 74 | 2018 |
| A Variational Auto-Encoder Model for Stochastic Point Processes N Mehrasa, A Abdu Jyothi, T Durand, J He, L Sigal, G Mori IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019 | 48 | 2019 |
| Generic Tubelet Proposals for Action Localization J He, MS Ibrahim, Z Deng, G Mori Winter Conference on Applications of Computer Vision, 2018 | 29 | 2018 |
| Piggyback gan: Efficient lifelong learning for image conditioned generation M Zhai, L Chen, J He, M Nawhal, F Tung, G Mori Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 26 | 2020 |
| Variational Autoencoders with Jointly Optimized Latent Dependency Structure J He, Y Gong, J Marino, G Mori, A Lehrmann International Conference on Learning Representations (ICLR), 2019 | 14 | 2019 |
| Object grounding via iterative context reasoning L Chen, M Zhai, J He, G Mori Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 11 | 2019 |
| Improving sequential latent variable models with autoregressive flows J Marino, L Chen, J He, S Mandt Symposium on advances in approximate bayesian inference, 1-16, 2020 | 10 | 2020 |
| Point process flows N Mehrasa, R Deng, MO Ahmed, B Chang, J He, T Durand, M Brubaker, ... arXiv preprint arXiv:1910.08281, 2019 | 10 | 2019 |
| 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 | 7 | 2021 |
| 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 |
| System and method for generative model for stochastic point processes N Mehrasa, AA Jyothi, T Durand, J He, M Gregory, M Ahmed, M Brubaker US Patent App. 16/685,327, 2020 | 4 | 2020 |
| 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 |
| Informed Priors for Deep Representation Learning J Bütepage, J He, C Zhang, L Sigal, G Mori, S Mandt Symposium on Advances in Approximate Bayesian Inference, 0 | 2* | |
| Agent Forecasting at Flexible Horizons using ODE Flows A Radovic, J He, J Ramanan, MA Brubaker, A Lehrmann ICML Workshop on Invertible Neural Networks, Normalizing Flows, and Explicit …, 2021 | 1 | 2021 |
| System and method for conditional marginal distributions at flexible evaluation horizons A Radovic, J He, JM Ramanan, MA Brubaker, ASM Lehrmann US Patent App. 17/750,335, 2022 | | 2022 |
| Theoretical and applicational advances in variational autoencoders J He Simon Fraser University, 2019 | | 2019 |
| LayoutVAE: Stochastic Scene Layout Generation From a Label Set A Abdu Jyothi, T Durand, J He, L Sigal, G Mori arXiv e-prints, arXiv: 1907.10719, 2019 | | 2019 |
| Learning from Partially-Observed Multimodal Data with Variational Autoencoders Y Gong, H Hajimirsadeghi, J He, M Nawhal, T Durand, G Mori | | |
Greg MoriResearch Director, Borealis AI; Professor, School of Computing Science, Simon Fraser UniversityVerified email at cs.sfu.ca
