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Chaochao Lu
Chaochao Lu
Shanghai AI Laboratory
Verified email at pjlab.org.cn - Homepage
Title
Cited by
Cited by
Year
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
4352015
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
1192017
Invariant Causal Representation Learning for Out-of-Distribution Generalization
C Lu, Y Wu, JM Hernández-Lobato, B Schölkopf
International Conference on Learning Representations, 2021
672021
Deconfounding Reinforcement Learning in Observational Settings
C Lu, B Schölkopf, JM Hernández-Lobato
arXiv preprint arXiv:1812.10576, 2018
662018
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
502021
Nonlinear Invariant Risk Minimization: A Causal Approach
C Lu, Y Wu, JM Hernández-Lobato, B Schölkopf
502021
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
472020
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
222022
Learning the Face Prior for Bayesian Face Recognition
C Lu, X Tang
in Proceedings of European Conference on Computer Vision (ECCV), 119-134, 2014
132014
Face Recognition Using Face Patch Networks
C Lu, D Zhao, X Tang
in Proceedings of IEEE International Conference on Computer Vision (ICCV …, 2013
122013
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
92023
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
92022
Interpreting Spatially Infinite Generative Models
C Lu, R Turner, Y Li, N Kushman
in Proceedings of ICML Workshop on Human Interpretability in Machine …, 2020
62020
Distribution-consistency Structural Causal Models
H Gong, C Lu, Y Zhang
arXiv preprint arXiv:2401.15911, 2024
12024
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
12024
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
12023
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
2024
ACAMDA: Improving Data Efficiency in Reinforcement Learning Through Guided Counterfactual Data Augmentation
Y Sun, E Wang, B Huang, C Lu, L Feng, C Sun, K Zhang
in Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI), 2024
2024
Introduction to Causal Reinforcement Learning
C Lu
Blogpost at causallu.com, 2018
2018
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