I Act Therefore I Am: When Is JEPA's Action-Conditioning Enough to Learn Causal Mechanisms?
Yuhang Liu, Zhuo Huang, Javen Qinfeng Shi
Concept Component Analysis: A Principled Approach for Concept Extraction in LLMs
Yuhang Liu, Erdun Gao, Dong Gong, Anton van den Hengel, Javen Qinfeng Shi
Bayesian Causal Experimental Design for CATE Estimation under Noncompliance
Erdun Gao, Yuanyuan Wang, Liang Zhang, Yuhang Liu, Haoxuan Li, Mingming Gong, Dino Sejdinovic.
Advances in Neural Information Processing Systems (NeurIPS), 2026.
Towards Identifiable Latent Additive Noise Models
Yuhang Liu, Zhen Zhang, Dong Gong, Erdun Gao, Biwei Huang, Mingming Gong, Anton van den Hengel, Kun Zhang, Javen Qinfeng Shi.
Advances in Neural Information Processing Systems (NeurIPS), 2026.
Learning Latent Dynamical Causal Processes for Single-Cell Perturbation Prediction
Wenkang Jiang, Yuhang Liu#, Erdun Gao, Ehsan Abbasnejad, Lina Yao, Javen Qinfeng Shi
SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2026
What Makes a Good Representation for Single-Cell Perturbation Prediction?
Wenkang Jiang, Yuhang Liu#, Yichao Cai, Erdun Gao, Jiayi Dong, Ehsan Abbasnejad, Lina Yao, Javen Qinfeng Shi,
International Conference on Machine Learning (ICML), 2026
The Geometric Mechanics of Contrastive Representation Learning: Alignment Potentials, Entropic Dispersion, and Cross-Modal Divergence
Yichao Cai, Zhen Zhang, Yuhang Liu, Javen Qinfeng Shi
International Conference on Machine Learning (ICML), 2026
Boundary Embedding Shaping with Adaptive Contrastive Learning for Graph Structural Disentanglement
Jiaqing Chen, Zidu Yin, Yichao Cai, Yuhang Liu, Zhen Zhang, Dong Gong, Javen Qinfeng Shi
International Conference on Machine Learning (ICML), 2026
Identifying Weight-Variant Latent Causal Models
Yuhang Liu, Zhen Zhang, Dong Gong, Mingming Gong, Biwei Huang, Anton van den Hengel, Kun Zhang, Javen Qinfeng Shi
Journal of Machine Learning Research (JMLR), 2026
I Predict Therefore I Am: Is Next Token Prediction Enough to Learn Human-Interpretable Concepts from Data?
Yuhang Liu, Dong Gong, Yichao Cai, Erdun Gao, Zhen Zhang, Biwei Huang, Mingming Gong, Anton van den Hengel, Javen Qinfeng Shi
International Conference on Learning Representations (ICLR), 2026
Beyond DAGs: A Latent Partial Causal Model for Multimodal Learning
Yuhang Liu, Zhen Zhang, Dong Gong, Erdun Gao, Biwei Huang, Mingming Gong, Anton van den Hengel, Kun Zhang, Javen Qinfeng Shi
International Conference on Learning Representations (ICLR), 2026
Model Inversion with Layer-Specific Modeling and Alignment for Data-Free Continual Learning
Ruilin Tong, Haodong Lu, Yuhang Liu, Dong Gong
Advances In Neural Information Processing Systems (NeurIPS), 2025
On the Value of Cross-Modal Misalignment in Multimodal Representation Learning
Yichao Cai*, Yuhang Liu*#, Erdun Gao, Tianjiao Jiang, Zhen Zhang, Anton van den Hengel, Javen Qinfeng Shi
Advances In Neural Information Processing Systems (NeurIPS), 2025
Causal Disentanglement and Cross-Modal Alignment for Enhanced Few-Shot Learning
Tianjiao Jiang, Zhen Zhang, Yuhang Liu#, Javen Qinfeng Shi
International Conference on Computer Vision (ICCV), 2025
Seeing Beyond Labels: Source-Free Domain Adaptation via Hypothesis Consolidation of Prediction Rationale
Yangyang Shu, Yuhang Liu, Xiaofeng Cao, Qi Chen, Bowen Zhang, Ziqin Zhou, Anton van den Hengel, Lingqiao Liu
Transactions on Machine Learning Research(TMLR), 2025.
Latent Covariate Shift: Unlocking Partial Identifiability for Multi-Source Domain Adaptation
Yuhang Liu, Zhen Zhang, Dong Gong, Mingming Gong, Biwei Huang, Anton van den Hengel, Kun Zhang, Javen Qinfeng Shi
Transactions on Machine Learning Research(TMLR), 2025.
Coreset Selection via Reducible Loss in Continual Learning
Ruilin Tong, Yuhang Liu, Javen Qinfeng Shi, Dong Gong,
International Conference on Learning Representations (ICLR), 2025.
Analytic DAG Constraints for Differentiable DAG Learning
Zhen Zhang, Ignavier Ng, Dong Gong, Yuhang Liu, Mingming Gong, Biwei Huang, Kun Zhang, Anton van den Hengel, Javen Qinfeng Shi
International Conference on Learning Representations (ICLR), 2025.
Rethinking State Disentanglement in Causal Reinforcement Learning
Haiyao Cao, Zhen Zhang, Panpan Cai, Yuhang Liu, Jinan Zou, Ehsan Abbasnejad, Biwei Huang, Mingming Gong, Anton van den Hengel, Javen Qinfeng Shi, https://arxiv.org/abs/2408.13498, 2024
Uncertainty estimation in HDR imaging with Bayesian neural networks
Qingsen Yan, Haishen Wang , Yifan Ma, Yuhang Liu, Wei Dong , Marcin Woźniak, Yanning Zhang,
Pattern Recognition (PR), 2024.
InvariantStock: Learning Invariant Features for Mastering the Shifting Market
Haiyao Cao, Jinan Zou, Yuhang Liu, Zhen Zhang, Ehsan Abbasnejad, Anton van den Hengel, Javen Qinfeng Shi,
Transactions on Machine Learning Research (TMLR), 2024.
CLAP: Isolating Content from Style through Contrastive Learning with Augmented Prompts
Yichao Cai, Yuhang Liu, Zhen Zhang, Javen Qinfeng Shi,
European Conference on Computer Vision (ECCV), 2024
Identifiable Latent Polynomial Causal Models Through the Lens of Change
Yuhang Liu, Zhen Zhang, Dong Gong, Mingming Gong, Biwei Huang, Anton van den Hengel, Kun Zhang, Javen Qinfeng Shi,
International Conference on Learning Representations (ICLR), 2024.
Truncated Matrix Power Iteration for Differentiable DAG Learning
Zhen Zhang, Ignavier Ng, Dong Gong, Yuhang Liu, Ehsan M Abbasnejad, Mingming Gong, Kun Zhang, Javen Qingfeng Shi,
Advances In Neural Information Processing Systems (NeurIPS) 2022
Learning Bayesian Sparse Networks with Full Experience Replay for Continual Learning
Qingsen Yan*, Dong Gong*, Yuhang Liu, Anton van den Hengel, Javen Qinfeng Shi,
IEEECVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022. (* Equal contribution)
A lightweight network for high dynamic range imaging
Qingsen Yan, Song Zhang, Weiye Chen, Yuhang Liu, Zhen Zhang, Yanning Zhang, Javen Qinfeng Shi, Dong Gong,,
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2022.
Variational Bayesian Dropout With a Hierarchical Prior
Yuhang Liu, Wenyong Dong, Lei Zhang, Dong Gong, Qinfeng Shi,
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019.
Bayesian Nonnegative Matrix Factorization With a Truncated Spike-and-slab Prior
Yuhang Liu, Wenyong Dong, Wanjuan Song, Lei Zhang,
IEEE International Conference on Multimedia and Expo (ICME), 2019.
Yuhang Liu, Wenyong Dong, Dong Gong, Lei Zhang, Qinfeng Shi,
European Conference on Computer Vision (ECCV), 2018.
Frame-Based Variational Bayesian Learning for Independent or Dependent Source Separation
Yuhang Liu, Wenyong Dong, and MengChu Zhou,
IEEE Transactions on Neural Networks and Learning Systems (TNNLS), VOL. 29, NO. 10, OCT. 2018.