Biwei Huang
According to our database1,
Biwei Huang
authored at least 46 papers
between 2015 and 2024.
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Bibliography
2024
Revealing Multimodal Contrastive Representation Learning through Latent Partial Causal Models.
CoRR, 2024
CoRR, 2024
ACAMDA: Improving Data Efficiency in Reinforcement Learning through Guided Counterfactual Data Augmentation.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024
2023
CoRR, 2023
CoRR, 2023
Generalized Independent Noise Condition for Estimating Causal Structure with Latent Variables.
CoRR, 2023
GRD: A Generative Approach for Interpretable Reward Redistribution in Reinforcement Learning.
CoRR, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the International Conference on Machine Learning, 2022
Action-Sufficient State Representation Learning for Control with Structural Constraints.
Proceedings of the International Conference on Machine Learning, 2022
Proceedings of the Tenth International Conference on Learning Representations, 2022
2021
CoRR, 2021
DeepTrader: A Deep Reinforcement Learning Approach for Risk-Return Balanced Portfolio Management with Market Conditions Embedding.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021
2020
CoRR, 2020
Generalized Independent Noise Condition for Estimating Linear Non-Gaussian Latent Variable Graphs.
CoRR, 2020
Generalized Independent Noise Condition for Estimating Latent Variable Causal Graphs.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020
2019
Diagnosis of Autism Spectrum Disorder by Causal Influence Strength Learned from Resting-State fMRI Data.
CoRR, 2019
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Causal Discovery and Forecasting in Nonstationary Environments with State-Space Models.
Proceedings of the 36th International Conference on Machine Learning, 2019
2018
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018
2017
Causal Discovery from Nonstationary/Heterogeneous Data: Skeleton Estimation and Orientation Determination.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017
Proceedings of the 2017 IEEE International Conference on Data Mining, 2017
2016
On the Identifiability and Estimation of Functional Causal Models in the Presence of Outcome-Dependent Selection.
Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence, 2016
2015
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015