Rui Shu
Cited by
Cited by
SHANK3 and IGF1 restore synaptic deficits in neurons from 22q13 deletion syndrome patients
A Shcheglovitov, O Shcheglovitova, M Yazawa, T Portmann, R Shu, ...
Nature 503 (7475), 267-271, 2013
A DIRT-T Approach to Unsupervised Domain Adaptation
R Shu, HH Bui, H Narui, S Ermon
International Conference on Learning Representations (ICLR), 2018
Constructing unrestricted adversarial examples with generative models
Y Song, R Shu, N Kushman, S Ermon
Advances in Neural Information Processing Systems 31, 2018
Weakly supervised disentanglement with guarantees
R Shu, Y Chen, A Kumar, S Ermon, B Poole
arXiv preprint arXiv:1910.09772, 2019
Robust locally-linear controllable embedding
E Banijamali, R Shu, M Ghavamzadeh, H Bui, A Ghodsi
International Conference on Artificial Intelligence and Statistics (AISTATS), 2017
Amortized Inference Regularization
R Shu, HH Bui, S Zhao, MJ Kochenderfer, S Ermon
Neural Information Processing Systems (NIPS), 2018
INF2-mediated severing through actin filament encirclement and disruption
PS Gurel, P Ge, EE Grintsevich, R Shu, L Blanchoin, ZH Zhou, E Reisler, ...
Current Biology 24 (2), 156-164, 2014
Fair generative modeling via weak supervision
K Choi, A Grover, T Singh, R Shu, S Ermon
International Conference on Machine Learning, 1887-1898, 2020
Alignflow: Cycle consistent learning from multiple domains via normalizing flows
A Grover, C Chute, R Shu, Z Cao, S Ermon
Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 4028-4035, 2020
Assembly and turnover of short actin filaments by the formin INF2 and profilin
PS Gurel, A Mu, B Guo, R Shu, DF Mierke, HN Higgs
Journal of Biological Chemistry 290 (37), 22494-22506, 2015
Bottleneck conditional density estimation
R Shu, HH Bui, M Ghavamzadeh
International Conference on Machine Learning (ICML), 2016
Monitoring ATP hydrolysis and ATPase inhibitor screening using 1H NMR
B Guo, PS Gurel, R Shu, HN Higgs, M Pellegrini, DF Mierke
Chemical Communications 50 (81), 12037-12039, 2014
Stochastic video prediction with conditional density estimation
R Shu, J Brofos, F Zhang, HH Bui, M Ghavamzadeh, M Kochenderfer
ECCV Workshop on Action and Anticipation for Visual Learning 2, 2, 2016
AC-GAN Learns a Biased Distribution
R Shu, H Bui, S Ermon
NIPS Workshop on Bayesian Deep Learning, 2017
Generative Adversarial Examples
Y Song, R Shu, N Kushman, S Ermon
Neural Information Processing Systems (NIPS), 2018
Prediction, consistency, curvature: Representation learning for locally-linear control
N Levine, Y Chow, R Shu, A Li, M Ghavamzadeh, H Bui
arXiv preprint arXiv:1909.01506, 2019
Bayesian optimization and attribute adjustment
S Eismann, D Levy, R Shu, S Bartzsch, S Ermon
UAI, 2018
Temporal predictive coding for model-based planning in latent space
TD Nguyen, R Shu, T Pham, H Bui, S Ermon
International Conference on Machine Learning, 8130-8139, 2021
Anytime sampling for autoregressive models via ordered autoencoding
Y Xu, Y Song, S Garg, L Gong, R Shu, A Grover, S Ermon
arXiv preprint arXiv:2102.11495, 2021
Predictive coding for locally-linear control
R Shu, T Nguyen, Y Chow, T Pham, K Than, M Ghavamzadeh, S Ermon, ...
International Conference on Machine Learning, 8862-8871, 2020
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