| Probabilistic Video Generation using Holistic Attribute Control J He, A Lehrmann, J Marino, G Mori, L Sigal European Conference on Computer Vision, 2018 | 38 | 2018 |
| Lifelong gan: Continual learning for conditional image generation M Zhai, L Chen, F Tung, J He, M Nawhal, G Mori Proceedings of the IEEE International Conference on Computer Vision, 2759-2768, 2019 | 33 | 2019 |
| Layoutvae: Stochastic scene layout generation from a label set AA Jyothi, T Durand, J He, L Sigal, G Mori Proceedings of the IEEE International Conference on Computer Vision, 9895-9904, 2019 | 24 | 2019 |
| Generic Tubelet Proposals for Action Localization J He, MS Ibrahim, Z Deng, G Mori Winter Conference on Applications of Computer Vision, 2018 | 20 | 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 | 15 | 2019 |
| 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 | 5 | 2019 |
| Variational selective autoencoder Y Gong, H Hajimirsadeghi, J He, M Nawhal, T Durand, G Mori Symposium on Advances in Approximate Bayesian Inference, 1-17, 2020 | 3 | 2020 |
| Point Process Flows N Mehrasa, R Deng, MO Ahmed, B Chang, J He, T Durand, M Brubaker, ... arXiv preprint arXiv:1910.08281, 2019 | 3 | 2019 |
| Object grounding via iterative context reasoning L Chen, M Zhai, J He, G Mori Proceedings of the IEEE International Conference on Computer Vision …, 2019 | 3 | 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 | 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* | |
| 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 | | 2020 |
| Piggyback GAN: Efficient Lifelong Learning for Image Conditioned Generation M Zhai, L Chen, J He, M Nawhal, F Tung, G Mori European Conference on Computer Vision, 397-413, 2020 | | 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 | | 2020 |
| Theoretical and applicational advances in variational autoencoders J He Applied Sciences: School of Computing Science, 2019 | | 2019 |
| Arbitrarily-conditioned Data Imputation M Carvalho, T Durand, J He, N Mehrasa, G Mori | | 2019 |
| Learning from Partially-Observed Multimodal Data with Variational Autoencoders Y Gong, H Hajimirsadeghi, J He, M Nawhal, T Durand, G Mori | | 2019 |
| LayoutVAE: Stochastic Scene Layout Generation From a Label Set A Abdu Jyothi, T Durand, J He, L Sigal, G Mori arXiv, arXiv: 1907.10719, 2019 | | 2019 |
| Variational Latent Dependency Learning J He, Y Gong, J Marino, G Mori, A Lehrmann Bayesian Deep Learning Workshop (NeurIPS '18), 0 | | |
Greg MoriResearch Director, Borealis AI; Professor, School of Computing Science, Simon Fraser UniversityVerified email at cs.sfu.ca
