Gao, Tian

52 publications

AAAI 2025 BEV-TSR: Text-Scene Retrieval in BEV Space for Autonomous Driving Tao Tang, Dafeng Wei, Zhengyu Jia, Tian Gao, Changwei Cai, Chengkai Hou, Peng Jia, Kun Zhan, Haiyang Sun, Jingchen Fan, Yixing Zhao, Xiaodan Liang, Xianpeng Lang, Yang Wang

CVPR 2025 BHViT: Binarized Hybrid Vision Transformer Tian Gao, Yu Zhang, Zhiyuan Zhang, Huajun Liu, Kaijie Yin, Chengzhong Xu, Hui Kong

ICCV 2025 Information-Bottleneck Driven Binary Neural Network for Change Detection Kaijie Yin, Zhiyuan Zhang, Shu Kong, Tian Gao, Cheng-Zhong Xu, Hui Kong

AISTATS 2025 Integer Programming Based Methods and Heuristics for Causal Graph Learning Sanjeeb Dash, Joao Goncalves, Tian Gao

ICLR 2025 Justice or Prejudice? Quantifying Biases in LLM-as-a-Judge Jiayi Ye, Yanbo Wang, Yue Huang, Dongping Chen, Qihui Zhang, Nuno Moniz, Tian Gao, Werner Geyer, Chao Huang, Pin-Yu Chen, Nitesh V Chawla, Xiangliang Zhang

NeurIPS 2025 Meta-D2AG: Causal Graph Learning with Interventional Dynamic Data Tian Gao, Songtao Lu, Junkyu Lee, Elliot Nelson, Debarun Bhattacharjya, Yue Yu, Miao Liu

ICLRW 2025 Policy-Agnostic RL: Offline RL and Online RL Fine-Tuning of Any Class and Backbone Max Sobol Mark, Tian Gao, Georgia Gabriela Sampaio, Mohan Kumar Srirama, Archit Sharma, Chelsea Finn, Aviral Kumar

AISTATS 2025 Q-Function Decomposition with Intervention Semantics for Factored Action Spaces Junkyu Lee, Tian Gao, Elliot Nelson, Miao Liu, Debarun Bhattacharjya, Songtao Lu

AAAI 2024 CHRONOS: A Schema-Based Event Understanding and Prediction System Maria Chang, Achille Fokoue, Rosario Uceda-Sosa, Parul Awasthy, Ken Barker, Sadhana Kumaravel, Oktie Hassanzadeh, Elton F. S. Soares, Tian Gao, Debarun Bhattacharjya, Radu Florian, Salim Roukos

AAAI 2024 Effective Causal Discovery Under Identifiable Heteroscedastic Noise Model Naiyu Yin, Tian Gao, Yue Yu, Qiang Ji

ECCV 2024 Integrating Markov Blanket Discovery into Causal Representation Learning for Domain Generalization Naiyu Yin, Hanjing Wang, Yue Yu, Tian Gao, Amit Dhurandhar, Qiang Ji

NeurIPSW 2024 Justice or Prejudice? Quantifying Biases in LLM-as-a-Judge Jiayi Ye, Yanbo Wang, Yue Huang, Dongping Chen, Qihui Zhang, Nuno Moniz, Tian Gao, Werner Geyer, Chao Huang, Pin-Yu Chen, Nitesh V Chawla, Xiangliang Zhang

NeurIPS 2024 Nonlocal Attention Operator: Materializing Hidden Knowledge Towards Interpretable Physics Discovery Yue Yu, Ning Liu, Fei Lu, Tian Gao, Siavash Jafarzadeh, Stewart Silling

AISTATS 2024 Theory-Guided Message Passing Neural Network for Probabilistic Inference Zijun Cui, Hanjing Wang, Tian Gao, Kartik Talamadupula, Qiang Ji

CVPR 2023 An Actor-Centric Causality Graph for Asynchronous Temporal Inference in Group Activity Zhao Xie, Tian Gao, Kewei Wu, Jiao Chang

IJCAI 2023 Approximate Inference in Logical Credal Networks Radu Marinescu, Haifeng Qian, Alexander G. Gray, Debarun Bhattacharjya, Francisco Barahona, Tian Gao, Ryan Riegel

CVPR 2023 Biomechanics-Guided Facial Action Unit Detection Through Force Modeling Zijun Cui, Chenyi Kuang, Tian Gao, Kartik Talamadupula, Qiang Ji

NeurIPSW 2023 Causal Markov Blanket Representation Learning for Out-of-Distribution Generalization Naiyu Yin, Hanjing Wang, Tian Gao, Amit Dhurandhar, Qiang Ji

AAAI 2023 Concurrent Multi-Label Prediction in Event Streams Xiao Shou, Tian Gao, Dharmashankar Subramanian, Debarun Bhattacharjya, Kristin P. Bennett

CLeaR 2023 Influence-Aware Attention for Multivariate Temporal Point Processes Xiao Shou, Tian Gao, Dharmashankar Subramanian, Debarun Bhattacharjya, Kristin Bennett

NeurIPS 2023 Pairwise Causality Guided Transformers for Event Sequences Xiao Shou, Debarun Bhattacharjya, Tian Gao, Dharmashankar Subramanian, Oktie Hassanzadeh, Kristin P Bennett

ICML 2023 Probabilistic Attention-to-Influence Neural Models for Event Sequences Xiao Shou, Debarun Bhattacharjya, Tian Gao, Dharmashankar Subramanian, Oktie Hassanzadeh, Kristin Bennett

AAAI 2023 Score-Based Learning of Graphical Event Models with Background Knowledge Augmentation Debarun Bhattacharjya, Tian Gao, Dharmashankar Subramanian, Xiao Shou

ICML 2022 IDYNO: Learning Nonparametric DAGs from Interventional Dynamic Data Tian Gao, Debarun Bhattacharjya, Elliot Nelson, Miao Liu, Yue Yu

CoRL 2022 Learning and Retrieval from Prior Data for Skill-Based Imitation Learning Soroush Nasiriany, Tian Gao, Ajay Mandlekar, Yuke Zhu

UAI 2022 Linearizing Contextual Bandits with Latent State Dynamics Elliot Nelson, Debarun Bhattacharjya, Tian Gao, Miao Liu, Djallel Bouneffouf, Pascal Poupart

NeurIPS 2022 Logical Credal Networks Radu Marinescu, Haifeng Qian, Alexander G. Gray, Debarun Bhattacharjya, Francisco Barahona, Tian Gao, Ryan Riegel, Pravinda Sahu

ICML 2022 Phasic Self-Imitative Reduction for Sparse-Reward Goal-Conditioned Reinforcement Learning Yunfei Li, Tian Gao, Jiaqi Yang, Huazhe Xu, Yi Wu

CLeaR 2022 Process Independence Testing in Proximal Graphical Event Models Debarun Bhattacharjya, Karthikeyan Shanmugam, Tian Gao, Dharmashankar Subramanian

UAI 2022 Variational Message Passing Neural Network for Maximum-a-Posteriori (MAP) Inference Zijun Cui, Hanjing Wang, Tian Gao, Kartik Talamadupula, Qiang Ji

NeurIPS 2021 Causal Inference for Event Pairs in Multivariate Point Processes Tian Gao, Dharmashankar Subramanian, Debarun Bhattacharjya, Xiao Shou, Nicholas Mattei, Kristin P Bennett

ICML 2021 DAGs with No Curl: An Efficient DAG Structure Learning Approach Yue Yu, Tian Gao, Naiyu Yin, Qiang Ji

ICML 2021 Integer Programming for Causal Structure Learning in the Presence of Latent Variables Rui Chen, Sanjeeb Dash, Tian Gao

AAAI 2021 Ordinal Historical Dependence in Graphical Event Models with Tree Representations Debarun Bhattacharjya, Tian Gao, Dharmashankar Subramanian

AAAI 2021 Type-Augmented Relation Prediction in Knowledge Graphs Zijun Cui, Pavan Kapanipathi, Kartik Talamadupula, Tian Gao, Qiang Ji

AAAI 2020 A Multi-Channel Neural Graphical Event Model with Negative Evidence Tian Gao, Dharmashankar Subramanian, Karthikeyan Shanmugam, Debarun Bhattacharjya, Nicholas Mattei

IJCAI 2020 Cause-Effect Association Between Event Pairs in Event Datasets Debarun Bhattacharjya, Tian Gao, Nicholas Mattei, Dharmashankar Subramanian

AISTATS 2020 Characterization of Overlap in Observational Studies Michael Oberst, Fredrik Johansson, Dennis Wei, Tian Gao, Gabriel Brat, David Sontag, Kush Varshney

NeurIPS 2020 DAGs with No Fears: A Closer Look at Continuous Optimization for Learning Bayesian Networks Dennis Wei, Tian Gao, Yue Yu

AAAI 2020 Event-Driven Continuous Time Bayesian Networks Debarun Bhattacharjya, Karthikeyan Shanmugam, Tian Gao, Nicholas Mattei, Kush R. Varshney, Dharmashankar Subramanian

PGM 2020 Hawkesian Graphical Event Models Xiufan Yu, Karthikeyan Shanmugam, Debarun Bhattacharjya, Tian Gao, Dharmashankar Subramanian, Lingzhou Xue

IJCAI 2020 Order-Dependent Event Models for Agent Interactions Debarun Bhattacharjya, Tian Gao, Dharmashankar Subramanian

IJCAI 2020 State Variable Effects in Graphical Event Models Debarun Bhattacharjya, Dharmashankar Subramanian, Tian Gao

AAAI 2019 A Sequential Set Generation Method for Predicting Set-Valued Outputs Tian Gao, Jie Chen, Vijil Chenthamarakshan, Michael Witbrock

ICML 2019 DAG-GNN: DAG Structure Learning with Graph Neural Networks Yue Yu, Jie Chen, Tian Gao, Mo Yu

ICML 2019 Generalized Linear Rule Models Dennis Wei, Sanjeeb Dash, Tian Gao, Oktay Gunluk

ICML 2018 Parallel Bayesian Network Structure Learning Tian Gao, Dennis Wei

NeurIPS 2018 Proximal Graphical Event Models Debarun Bhattacharjya, Dharmashankar Subramanian, Tian Gao

ICML 2017 Local-to-Global Bayesian Network Structure Learning Tian Gao, Kshitij Fadnis, Murray Campbell

IJCAI 2016 Constrained Local Latent Variable Discovery Tian Gao, Qiang Ji

NeurIPS 2015 Local Causal Discovery of Direct Causes and Effects Tian Gao, Qiang Ji

ICCV 2015 Structured Feature Selection Tian Gao, Ziheng Wang, Qiang Ji