Biwei Huang

802 total citations
17 papers, 261 citations indexed

About

Biwei Huang is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Management Science and Operations Research. According to data from OpenAlex, Biwei Huang has authored 17 papers receiving a total of 261 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 3 papers in Computational Theory and Mathematics and 3 papers in Management Science and Operations Research. Recurrent topics in Biwei Huang's work include Bayesian Modeling and Causal Inference (8 papers), Rough Sets and Fuzzy Logic (3 papers) and Domain Adaptation and Few-Shot Learning (3 papers). Biwei Huang is often cited by papers focused on Bayesian Modeling and Causal Inference (8 papers), Rough Sets and Fuzzy Logic (3 papers) and Domain Adaptation and Few-Shot Learning (3 papers). Biwei Huang collaborates with scholars based in United States, Germany and Australia. Biwei Huang's co-authors include Kun Zhang, Clark Glymour, Bernhard Schölkopf, Jiji Zhang, Shikui Tu, Lei Xu, Zhicheng Wang, Rubén Sánchez-Romero, Yizhu Lin and Joseph Ramsey and has published in prestigious journals such as IEEE Transactions on Multimedia, Network Neuroscience and Minerva Access (University of Melbourne).

In The Last Decade

Biwei Huang

15 papers receiving 256 citations

Peers

Countries citing papers authored by Biwei Huang

Since Specialization

Citations

This map shows the geographic impact of Biwei Huang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Biwei Huang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Biwei Huang more than expected).

Fields of papers citing papers by Biwei Huang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Biwei Huang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Biwei Huang. The network helps show where Biwei Huang may publish in the future.

Co-authorship network of co-authors of Biwei Huang

This figure shows the co-authorship network connecting the top 25 collaborators of Biwei Huang. A scholar is included among the top collaborators of Biwei Huang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Biwei Huang. Biwei Huang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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17 of 17 papers shown

#	Work	Indexed citations
1	HCVP: Leveraging Hierarchical Contrastive Visual Prompt for Domain Generalization 2024 ·IEEE Transactions on Multimedia ·Guanglin Zhou, Zhongyi Han, Shiming Chen, Biwei Huang, Liming Zhu, Tongliang Liu, Lina Yao, Kun Zhang	1
2	ACAMDA: Improving Data Efficiency in Reinforcement Learning through Guided Counterfactual Data Augmentation 2024 ·Proceedings of the AAAI Conference on Artificial Intelligence ·(unknown), (unknown), Biwei Huang, Chaochao Lu, Feng Lu, Changyin Sun, Kun Zhang	1
3	Learning Discrete Concepts in Latent Hierarchical Models 2024 ·Guangyi Chen, Yuejie Chi, Biwei Huang, Lingjing Kong, Eric P. Xing, Kun Zhang	1
4	Interpretable Reward Redistribution in Reinforcement Learning: A Causal Approach 2023 ·(unknown), (unknown), Biwei Huang, (unknown), (unknown), (unknown), Yudi Zhang	0
5	Factored Adaptation for Non-Stationary Reinforcement Learning 2022 ·(unknown), Biwei Huang, Sara Magliacane, (unknown)	0
6	DeepTrader: A Deep Reinforcement Learning Approach for Risk-Return Balanced Portfolio Management with Market Conditions Embedding 2021 ·Proceedings of the AAAI Conference on Artificial Intelligence ·Zhicheng Wang, Biwei Huang, Shikui Tu, Kun Zhang, Lei Xu	62
7	Domain Adaptation as a Problem of Inference on Graphical Models 2020 ·Neural Information Processing Systems ·Kun Zhang, Mingming Gong, Petar Stojanov, Biwei Huang, Qingsong Liu, Clark Glymour	1
8	Causal Discovery from Multiple Data Sets with Non-Identical Variable Sets 2020 ·Proceedings of the AAAI Conference on Artificial Intelligence ·Biwei Huang, Kun Zhang, Mingming Gong, Clark Glymour	8
9	Causal Discovery and Hidden Driving Force Estimation from Nonstationary/Heterogeneous Data 2019 ·arXiv (Cornell University) ·Biwei Huang, Kun Zhang, Jiji Zhang, Joseph Ramsey, Bernhard Schölkopf, Clark Glymour	2
10	Specific and Shared Causal Relation Modeling and Mechanism-Based Clustering 2019 ·Minerva Access (University of Melbourne) ·Biwei Huang, Kun Zhang, Pengtao Xie, Mingming Gong, Eric P. Xing, Clark Glymour	5
11	Estimating feedforward and feedback effective connections from fMRI time series: Assessments of statistical methods 2018 ·Network Neuroscience ·Rubén Sánchez-Romero, Joseph Ramsey, Kun Zhang, Madelyn Glymour, Biwei Huang, Clark Glymour	49
12	Multi-domain Causal Structure Learning in Linear Systems. 2018 ·PubMed ·(unknown), Negar Kiyavash, Biwei Huang, Kun Zhang	8
13	Generalized Score Functions for Causal Discovery 2018 ·PubMed ·Biwei Huang, Kun Zhang, Yizhu Lin, Bernhard Schölkopf, Clark Glymour	51
14	Behind Distribution Shift: Mining Driving Forces of Changes and Causal Arrows 2017 ·PubMed ·Biwei Huang, Kun Zhang, Jiji Zhang, Rubén Sánchez-Romero, Clark Glymour, Bernhard Schölkopf	16
15	Causal Discovery from Nonstationary/Heterogeneous Data: Skeleton Estimation and Orientation Determination 2017 ·Digital Commons - Lingnan (Lingnan University) ·Kun Zhang, Biwei Huang, Jiji Zhang, Clark Glymour, Bernhard Schölkopf	47
16	On the identifiability and estimation of functional causal models in the presence of outcome-dependent selection 2016 ·Digital Commons - Lingnan (Lingnan University) ·Kun Zhang, Jiji Zhang, Biwei Huang, Bernhard Schölkopf, Clark Glymour	2
17	Identification of Time-Dependent Causal Model: a gaussian process treatment 2015 ·MPG.PuRe (Max Planck Society) ·Biwei Huang, Kun Zhang, Bernhard Schölkopf	7

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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