Bo Chang
Bo Chang
Google DeepMind
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Cited by
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Reversible Architectures for Arbitrarily Deep Residual Neural Networks
B Chang, L Meng, E Haber, L Ruthotto, D Begert, E Holtham
AAAI Conference on Artificial Intelligence (AAAI), 2018
AntisymmetricRNN: A Dynamical System View on Recurrent Neural Networks
B Chang, M Chen, E Haber, EH Chi
International Conference on Learning Representations (ICLR), 2019
Multi-level Residual Networks from Dynamical Systems View
B Chang, L Meng, E Haber, F Tung, D Begert
International Conference on Learning Representations (ICLR), 2018
Generating Handwritten Chinese Characters using CycleGAN
B Chang, Q Zhang, S Pan, L Meng
IEEE Winter Conference on Applications of Computer Vision (WACV), 2018
Interpretable spatio-temporal attention for video action recognition
L Meng, B Zhao, B Chang, G Huang, W Sun, F Tung, L Sigal
Proceedings of the IEEE International Conference on Computer Vision …, 2019
Modular Generative Adversarial Networks
B Zhao, B Chang, Z Jie, L Sigal
European Conference on Computer Vision (ECCV), 2018
Convolutional neural networks combined with Runge–Kutta methods
M Zhu, B Chang, C Fu
Neural Computing and Applications, 1-15, 2022
Prediction based on conditional distributions of vine copulas
B Chang, H Joe
Computational Statistics & Data Analysis 139, 45-63, 2019
Modeling continuous stochastic processes with dynamic normalizing flows
R Deng, B Chang, MA Brubaker, G Mori, A Lehrmann
Conference on Neural Information Processing Systems (NeurIPS), 2020
User response models to improve a reinforce recommender system
M Chen, B Chang, C Xu, EH Chi
Proceedings of the 14th ACM international conference on web search and data …, 2021
Dynamical isometry and a mean field theory of LSTMs and GRUs
D Gilboa, B Chang, M Chen, G Yang, SS Schoenholz, EH Chi, ...
arXiv preprint arXiv:1901.08987, 2019
CopulaGNN: Towards Integrating Representational and Correlational Roles of Graphs in Graph Neural Networks
J Ma, B Chang, X Zhang, Q Mei
International Conference on Learning Representations (ICLR), 2021
Vine regression
RM Cooke, H Joe, B Chang
Resources for the Future Discussion Paper 15-52, 2015
Vine copula regression for observational studies
RM Cooke, H Joe, B Chang
AStA advances in statistical analysis 104, 141-167, 2020
Point process flows
N Mehrasa, R Deng, MO Ahmed, B Chang, J He, T Durand, M Brubaker, ...
arXiv preprint arXiv:1910.08281, 2019
Vine copula structure learning via Monte Carlo tree search
B Chang, S Pan, H Joe
International Conference on Artificial Intelligence and Statistics (AISTATS …, 2019
Learning to augment for casual user recommendation
J Wang, Y Le, B Chang, Y Wang, EH Chi, M Chen
Proceedings of the ACM Web Conference 2022, 2183-2194, 2022
Latent user intent modeling for sequential recommenders
B Chang, A Karatzoglou, Y Wang, C Xu, EH Chi, M Chen
Companion Proceedings of the ACM Web Conference 2023, 427-431, 2023
Copula diagnostics for asymmetries and conditional dependence
B Chang, H Joe
Journal of Applied Statistics 47 (9), 1587-1615, 2020
Vine regression with Bayes nets: A critical comparison with traditional approaches based on a case study on the effects of breastfeeding on IQ
RM Cooke, H Joe, B Chang
Risk Analysis 42 (6), 1294-1305, 2022
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