Tian Gao

According to our database, Tian Gao authored at least 22 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Learning Causal Graphs at Scale: A Foundation Model Approach.

Naiyu Yin, Tian Gao, Yue Yu

CoRR, June, 2025

Q-function Decomposition with Intervention Semantics for Factored Action Spaces.

Junkyu Lee, Tian Gao, Elliot Nelson, Miao Liu, Debarun Bhattacharjya, Songtao Lu

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025

2024

Identifying Sub-networks in Neural Networks via Functionally Similar Representations.

Tian Gao, Amit Dhurandhar, Karthikeyan Natesan Ramamurthy, Dennis Wei

CoRR, 2024

Disentangled Representation Learning for Parametric Partial Differential Equations.

Ning Liu, Lu Zhang, Tian Gao, Yue Yu

CoRR, 2024

Nonlocal Attention Operator: Materializing Hidden Knowledge Towards Interpretable Physics Discovery.

Yue Yu, Ning Liu, Fei Lu, Tian Gao, Siavash Jafarzadeh, Stewart A. Silling

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Efficient Nonlinear DAG Learning Under Projection Framework.

Naiyu Yin, Yue Yu, Tian Gao, Qiang Ji

Proceedings of the Pattern Recognition - 27th International Conference, 2024

Integrating Markov Blanket Discovery Into Causal Representation Learning for Domain Generalization.

Naiyu Yin, Hanjing Wang, Yue Yu, Tian Gao, Amit Dhurandhar, Qiang Ji

Proceedings of the Computer Vision - ECCV 2024, 2024

Effective Causal Discovery under Identifiable Heteroscedastic Noise Model.

Naiyu Yin, Tian Gao, Yue Yu, Qiang Ji

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Causal Discovery under Identifiable Heteroscedastic Noise Model.

Naiyu Yin, Tian Gao, Yue Yu, Qiang Ji

CoRR, 2023

MetaNO: How to Transfer Your Knowledge on Learning Hidden Physics.

Lu Zhang, Huaiqian You, Tian Gao, Mo Yu, Chung-Hao Lee, Yue Yu

CoRR, 2023

2022

Nonlocal kernel network (NKN): A stable and resolution-independent deep neural network.

Huaiqian You, Yue Yu, Marta D'Elia, Tian Gao, Stewart Silling

J. Comput. Phys., 2022

Linearizing contextual bandits with latent state dynamics.

Elliot Nelson, Debarun Bhattacharjya, Tian Gao, Miao Liu, Djallel Bouneffouf, Pascal Poupart

Proceedings of the Uncertainty in Artificial Intelligence, 2022

IDYNO: Learning Nonparametric DAGs from Interventional Dynamic Data.

Tian Gao, Debarun Bhattacharjya, Elliot Nelson, Miao Liu, Yue Yu

Proceedings of the International Conference on Machine Learning, 2022

2021

DAGs with No Curl: An Efficient DAG Structure Learning Approach.

Yue Yu, Tian Gao, Naiyu Yin, Qiang Ji

Proceedings of the 38th International Conference on Machine Learning, 2021

Timeline Summarization based on Event Graph Compression via Time-Aware Optimal Transport.

Manling Li, Tengfei Ma, Mo Yu, Lingfei Wu, Tian Gao, Heng Ji, Kathleen R. McKeown

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

2020

DAGs with No Fears: A Closer Look at Continuous Optimization for Learning Bayesian Networks.

Dennis Wei, Tian Gao, Yue Yu

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

MCMH: Learning Multi-Chain Multi-Hop Rules for Knowledge Graph Reasoning.

Lu Zhang, Mo Yu, Tian Gao, Yue Yu

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

2019

DAG-GNN: DAG Structure Learning with Graph Neural Networks.

Yue Yu, Jie Chen, Tian Gao, Mo Yu

Proceedings of the 36th International Conference on Machine Learning, 2019

PEARL: Prototype Learning via Rule Learning.

Tianfan Fu, Tian Gao, Cao Xiao, Tengfei Ma, Jimeng Sun

Proceedings of the 10th ACM International Conference on Bioinformatics, 2019

Do Multi-hop Readers Dream of Reasoning Chains?

Haoyu Wang, Mo Yu, Xiaoxiao Guo, Rajarshi Das, Wenhan Xiong, Tian Gao

Proceedings of the 2nd Workshop on Machine Reading for Question Answering, 2019

Multi-step Entity-centric Information Retrieval for Multi-Hop Question Answering.

Rajarshi Das, Ameya Godbole, Dilip Kavarthapu, Zhiyu Gong, Abhishek Singhal, Mo Yu, Xiaoxiao Guo, Tian Gao, Hamed Zamani, Manzil Zaheer, Andrew McCallum

Proceedings of the 2nd Workshop on Machine Reading for Question Answering, 2019

A Sequential Set Generation Method for Predicting Set-Valued Outputs.

Tian Gao, Jie Chen, Vijil Chenthamarakshan, Michael Witbrock

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019