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Jiawei He
Jiawei He
Research, Borealis AI
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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
1862019
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
1192019
Probabilistic Video Generation using Holistic Attribute Control
J He, A Lehrmann, J Marino, G Mori, L Sigal
European Conference on Computer Vision, 2018
792018
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
612019
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
352020
Generic Tubelet Proposals for Action Localization
J He, MS Ibrahim, Z Deng, G Mori
Winter Conference on Applications of Computer Vision, 2018
332018
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
212019
Point process flows
N Mehrasa, R Deng, MO Ahmed, B Chang, J He, T Durand, M Brubaker, ...
arXiv preprint arXiv:1910.08281, 2019
152019
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
142021
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
142020
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
132019
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
112020
Variational selective autoencoder
Y Gong, H Hajimirsadeghi, J He, M Nawhal, T Durand, G Mori
Second Symposium on Advances in Approximate Bayesian Inference, 2019
82019
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
52020
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
32021
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 conditional marginal distributions at flexible evaluation horizons
A Radovic, J He, JM Ramanan, MA Brubaker, ASM Lehrmann
US Patent App. 17/750,335, 2022
12022
Arbitrarily-conditioned Data Imputation
M Carvalho, T Durand, J He, N Mehrasa, G Mori
Second Symposium on Advances in Approximate Bayesian Inference, 2019
12019
Theoretical and applicational advances in variational autoencoders
J He
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
2019
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