| Surpassing human-level face verification performance on LFW with GaussianFace C Lu, X Tang in Proceedings of the 29th AAAI Conference on Artificial Intelligence (AAAI), 2015 | 442 | 2015 |
| Flexible Spatio-Temporal Networks for Video Prediction C Lu, M Hirsch, B Schölkopf The IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2017), 2017 | 122 | 2017 |
| Invariant Causal Representation Learning for Out-of-Distribution Generalization C Lu, Y Wu, JM Hernández-Lobato, B Schölkopf International Conference on Learning Representations, 2021 | 80 | 2021 |
| Deconfounding Reinforcement Learning in Observational Settings C Lu, B Schölkopf, JM Hernández-Lobato arXiv preprint arXiv:1812.10576, 2018 | 70 | 2018 |
| AdaRL: What, Where, and How to Adapt in Transfer Reinforcement Learning B Huang, F Feng, C Lu, S Magliacane, K Zhang International Conference on Learning Representations, 2021 | 56 | 2021 |
| Nonlinear Invariant Risk Minimization: A Causal Approach C Lu, Y Wu, JM Hernández-Lobato, B Schölkopf | 54 | 2021 |
| Sample-Efficient Reinforcement Learning via Counterfactual-Based Data Augmentation C Lu*, B Huang*, K Wang, JM Hernández-Lobato, K Zhang, B Schölkopf in Proceedings of Neural Information Processing Systems Workshop on Offline …, 2020 | 54 | 2020 |
| 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 | 26 | 2022 |
| Learning the Face Prior for Bayesian Face Recognition C Lu, X Tang in Proceedings of European Conference on Computer Vision (ECCV), 119-134, 2014 | 13 | 2014 |
| InfoPrompt: Information-Theoretic Soft Prompt Tuning for Natural Language Understanding J Wu, T Yu, R Wang, Z Song, R Zhang, H Zhao, C Lu, S Li, R Henao in Proceedings of the 37th Conference on Neural Information Processing …, 2023 | 12 | 2023 |
| Face Recognition Using Face Patch Networks C Lu, D Zhao, X Tang in Proceedings of IEEE International Conference on Computer Vision (ICCV …, 2013 | 12 | 2013 |
| Invariant Causal Representation Learning for Generalization in Imitation and Reinforcement Learning C Lu, JM Hernández-Lobato, B Schölkopf ICLR2022 Workshop on the Elements of Reasoning: Objects, Structure and Causality, 2022 | 10 | 2022 |
| From GPT-4 to Gemini and Beyond: Assessing the Landscape of MLLMs on Generalizability, Trustworthiness and Causality through Four Modalities C Lu, C Qian, G Zheng, H Fan, H Gao, J Zhang, J Shao, J Deng, J Fu, ... arXiv preprint arXiv:2401.15071, 2024 | 7 | 2024 |
| Interpreting Spatially Infinite Generative Models C Lu, R Turner, Y Li, N Kushman in Proceedings of ICML Workshop on Human Interpretability in Machine …, 2020 | 6 | 2020 |
| ConditionVideo: Training-Free Condition-Guided Text-to-Video Generation B Peng, X Chen, Y Wang, C Lu, Y Qiao in Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI), 2024 | 4 | 2024 |
| Causal Evaluation of Language Models S Chen, B Peng, M Chen, R Wang, M Xu, X Zeng, R Zhao, S Zhao, Y Qiao, ... arXiv preprint arXiv:2405.00622, 2024 | 3 | 2024 |
| Quantifying and Mitigating Unimodal Biases in Multimodal Large Language Models: A Causal Perspective M Chen, Y Cao, Y Zhang, C Lu arXiv preprint arXiv:2403.18346, 2024 | 3 | 2024 |
| Few-Shot Composition Learning for Image Retrieval with Prompt Tuning J Wu, R Wang, H Zhao, R Zhang, C Lu, S Li, R Henao in Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI), 2023 | 2 | 2023 |
| ConditionVideo: Training-Free Condition-Guided Video Generation B Peng, X Chen, Y Wang, C Lu, Y Qiao Proceedings of the AAAI Conference on Artificial Intelligence 38 (5), 4459-4467, 2024 | 1 | 2024 |
| CELLO: Causal Evaluation of Large Vision-Language Models M Chen, B Peng, Y Zhang, C Lu arXiv preprint arXiv:2406.19131, 2024 | | 2024 |
Bernhard SchölkopfDirector, Max Planck Institute for Intelligent Systems & ELLIS Institute Tübingen; Professor at ETH在 tuebingen.mpg.de 的电子邮件经过验证
