Biwei Huang
Biwei Huang
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Cited by
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Causal discovery from heterogeneous/nonstationary data
B Huang, K Zhang, J Zhang, J Ramsey, R Sanchez-Romero, C Glymour, ...
Journal of Machine Learning Research 21 (89), 1-53, 2020
Causal discovery from nonstationary/heterogeneous data: Skeleton estimation and orientation determination
K Zhang, B Huang, J Zhang, C Glymour, B Schölkopf
IJCAI: Proceedings of the Conference 2017, 1347, 2017
Generalized Score Functions for Causal Discovery
B Huang, K Zhang, Y Lin, B Schölkopf, C Glymour
KDD'18, 2018
Tetrad—a toolbox for causal discovery
JD Ramsey, K Zhang, M Glymour, RS Romero, B Huang, I Ebert-Uphoff, ...
8th international workshop on climate informatics, 1-4, 2018
Generalized independent noise condition for estimating latent variable causal graphs
F Xie, R Cai, B Huang, C Glymour, Z Hao, K Zhang
Advances in neural information processing systems 33, 14891-14902, 2020
Estimating feedforward and feedback effective connections from fMRI time series: Assessments of statistical methods
R Sanchez-Romero, JD Ramsey, K Zhang, MRK Glymour, B Huang, ...
Network Neuroscience 3 (2), 274-306, 2019
Causal Discovery and Forecasting in Nonstationary Environments with State-Space Models
B Huang, K Zhang, M Gong, C Glymour
International Conference of Machine Learning, 2019, 2019
Domain adaptation as a problem of inference on graphical models
K Zhang, M Gong, P Stojanov, B Huang, Q Liu, C Glymour
Advances in neural information processing systems 33, 4965-4976, 2020
DeepTrader: a deep reinforcement learning approach for risk-return balanced portfolio management with market conditions Embedding
Z Wang, B Huang, S Tu, K Zhang, L Xu
Proceedings of the AAAI conference on artificial intelligence 35 (1), 643-650, 2021
Multi-domain causal structure learning in linear systems
AE Ghassami, N Kiyavash, B Huang, K Zhang
Advances in neural information processing systems 31, 2018
Adarl: What, where, and how to adapt in transfer reinforcement learning
B Huang, F Feng, C Lu, S Magliacane, K Zhang
arXiv preprint arXiv:2107.02729, 2021
Sample-efficient reinforcement learning via counterfactual-based data augmentation
C Lu, B Huang, K Wang, JM Hernández-Lobato, K Zhang, B Schölkopf
arXiv preprint arXiv:2012.09092, 2020
Identification of linear non-gaussian latent hierarchical structure
F Xie, B Huang, Z Chen, Y He, Z Geng, K Zhang
International Conference on Machine Learning, 24370-24387, 2022
Identification of time-dependent causal model: A gaussian process treatment
B Huang, K Zhang, B Schölkopf
Twenty-Fourth international joint conference on artificial intelligence, 2015
Latent hierarchical causal structure discovery with rank constraints
B Huang, CJH Low, F Xie, C Glymour, K Zhang
Advances in neural information processing systems 35, 5549-5561, 2022
Behind distribution shift: Mining driving forces of changes and causal arrows
B Huang, K Zhang, J Zhang, R Sanchez-Romero, C Glymour, B Schölkopf
2017 IEEE International Conference on Data Mining (ICDM), 913-918, 2017
Factored adaptation for non-stationary reinforcement learning
F Feng, B Huang, K Zhang, S Magliacane
Advances in Neural Information Processing Systems 35, 31957-31971, 2022
Causal-learn: Causal discovery in python
Y Zheng, B Huang, W Chen, J Ramsey, M Gong, R Cai, S Shimizu, ...
Journal of Machine Learning Research 25 (60), 1-8, 2024
Action-sufficient state representation learning for control with structural constraints
B Huang, C Lu, L Leqi, JM Hernández-Lobato, C Glymour, B Schölkopf, ...
International Conference on Machine Learning, 9260-9279, 2022
Causal generative domain adaptation networks
M Gong, K Zhang, B Huang, C Glymour, D Tao, K Batmanghelich
arXiv preprint arXiv:1804.04333, 2018
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