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ORCIDBiwei Huang
- > Home > Persons > Biwei Huang
Publications
- 2025
[c43]Zhen Zhang, Ignavier Ng, Dong Gong, Yuhang Liu, Mingming Gong, Biwei Huang, Kun Zhang, Anton van den Hengel, Javen Qinfeng Shi:
Analytic DAG Constraints for Differentiable DAG Learning. ICLR 2025- [c42]Yingyu Lin, Yuxing Huang, Wenqin Liu, Haoran Deng, Ignavier Ng, Kun Zhang, Mingming Gong, Yian Ma, Biwei Huang:
A Skewness-Based Criterion for Addressing Heteroscedastic Noise in Causal Discovery. ICLR 2025 - [c41]Parjanya Prajakta Prashant, Ignavier Ng, Kun Zhang, Biwei Huang:
Differentiable Causal Discovery for Latent Hierarchical Causal Models. ICLR 2025 - [i51]Minghao Fu
, Biwei Huang, Zijian Li, Yujia Zheng, Ignavier Ng, Yingyao Hu, Kun Zhang:
Identification of Nonparametric Dynamic Causal Structure and Latent Process in Climate System. CoRR abs/2501.12500 (2025) - [i49]Zhen Zhang, Ignavier Ng, Dong Gong, Yuhang Liu, Mingming Gong, Biwei Huang, Kun Zhang, Anton van den Hengel, Javen Qinfeng Shi:
Analytic DAG Constraints for Differentiable DAG Learning. CoRR abs/2503.19218 (2025) - 2024
- [c37]Ignavier Ng, Biwei Huang, Kun Zhang:
Structure Learning with Continuous Optimization: A Sober Look and Beyond. CLeaR 2024: 71-105 - [c35]Xinshuai Dong, Biwei Huang, Ignavier Ng, Xiangchen Song, Yujia Zheng, Songyao Jin, Roberto Legaspi, Peter Spirtes, Kun Zhang:
A Versatile Causal Discovery Framework to Allow Causally-Related Hidden Variables. ICLR 2024 - [c33]Loka Li, Ignavier Ng, Gongxu Luo, Biwei Huang, Guangyi Chen, Tongliang Liu, Bin Gu, Kun Zhang:
Federated Causal Discovery from Heterogeneous Data. ICLR 2024 - [c30]Ignavier Ng, Xinshuai Dong, Haoyue Dai, Biwei Huang, Peter Spirtes, Kun Zhang:
Score-Based Causal Discovery of Latent Variable Causal Models. ICML 2024 - [c27]Xinshuai Dong, Ignavier Ng, Biwei Huang, Yuewen Sun, Songyao Jin, Roberto Legaspi, Peter Spirtes, Kun Zhang:
On the Parameter Identifiability of Partially Observed Linear Causal Models. NeurIPS 2024 - [i40]Loka Li, Ignavier Ng, Gongxu Luo, Biwei Huang, Guangyi Chen, Tongliang Liu, Bin Gu, Kun Zhang:
Federated Causal Discovery from Heterogeneous Data. CoRR abs/2402.13241 (2024) - [i35]Xinshuai Dong, Ignavier Ng, Biwei Huang, Yuewen Sun, Songyao Jin, Roberto Legaspi, Peter Spirtes, Kun Zhang:
On the Parameter Identifiability of Partially Observed Linear Causal Models. CoRR abs/2407.16975 (2024) - [i31]Yingyu Lin, Yuxing Huang, Wenqin Liu, Haoran Deng, Ignavier Ng, Kun Zhang, Mingming Gong, Yi-An Ma, Biwei Huang:
A Skewness-Based Criterion for Addressing Heteroscedastic Noise in Causal Discovery. CoRR abs/2410.06407 (2024) - [i30]Kaifeng Jin, Ignavier Ng, Kun Zhang, Biwei Huang:
Revisiting Differentiable Structure Learning: Inconsistency of ℓ1 Penalty and Beyond. CoRR abs/2410.18396 (2024) - [i27]Parjanya Prajakta Prashant, Ignavier Ng, Kun Zhang, Biwei Huang:
Differentiable Causal Discovery For Latent Hierarchical Causal Models. CoRR abs/2411.19556 (2024) - 2023
- [i26]Ignavier Ng, Biwei Huang, Kun Zhang:
Structure Learning with Continuous Optimization: A Sober Look and Beyond. CoRR abs/2304.02146 (2023) - [i16]Xinshuai Dong, Biwei Huang, Ignavier Ng, Xiangchen Song, Yujia Zheng, Songyao Jin, Roberto Legaspi, Peter Spirtes, Kun Zhang:
A Versatile Causal Discovery Framework to Allow Causally-Related Hidden Variables. CoRR abs/2312.11001 (2023)
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