Tian Gao

34 papers A* 7A 2Journal 17Unranked 8
YearRankTypeTitle / Venue / Authors
2025 J jnl
Learning Causal Graphs at Scale: A Foundation Model Approach.
CoRR
Naiyu Yin, Tian Gao, Yue Yu
2025 A conf
Q-function Decomposition with Intervention Semantics for Factored Action Spaces.
AISTATS
Junkyu Lee, Tian Gao, Elliot Nelson, Miao Liu, Debarun Bhattacharjya, Songtao Lu
2025 J jnl
Q-function Decomposition with Intervention Semantics with Factored Action Spaces.
CoRR
Junkyu Lee, Tian Gao, Elliot Nelson, Miao Liu, Debarun Bhattacharjya, Songtao Lu
2025 J jnl
Resting Neurons, Active Insights: Improving Input Sparsification for Large Language Models.
CoRR
Haotian Xu, Tian Gao, Tsui-Wei Weng, Tengfei Ma
2024 J jnl
Disentangled Representation Learning for Parametric Partial Differential Equations.
CoRR
Ning Liu, Lu Zhang, Tian Gao, Yue Yu
2024 A* conf
Effective Causal Discovery under Identifiable Heteroscedastic Noise Model.
AAAI
Naiyu Yin, Tian Gao, Yue Yu, Qiang Ji
2024 — conf
Efficient Nonlinear DAG Learning Under Projection Framework.
ICPR (6)
Naiyu Yin, Yue Yu, Tian Gao, Qiang Ji
2024 J jnl
Identifying Sub-networks in Neural Networks via Functionally Similar Representations.
CoRR
Tian Gao, Amit Dhurandhar, Karthikeyan Natesan Ramamurthy, Dennis Wei
2024 — conf
Integrating Markov Blanket Discovery Into Causal Representation Learning for Domain Generalization.
ECCV (10)
Naiyu Yin, Hanjing Wang, Yue Yu, Tian Gao, Amit Dhurandhar, Qiang Ji
2024 A* conf
Nonlocal Attention Operator: Materializing Hidden Knowledge Towards Interpretable Physics Discovery.
NeurIPS
Yue Yu, Ning Liu, Fei Lu, Tian Gao, Siavash Jafarzadeh, Stewart A. Silling
2024 J jnl
Nonlocal Attention Operator: Materializing Hidden Knowledge Towards Interpretable Physics Discovery.
CoRR
Yue Yu, Ning Liu, Fei Lu, Tian Gao, Siavash Jafarzadeh, Stewart Silling
2023 J jnl
Causal Discovery under Identifiable Heteroscedastic Noise Model.
CoRR
Naiyu Yin, Tian Gao, Yue Yu, Qiang Ji
2023 J jnl
MetaNO: How to Transfer Your Knowledge on Learning Hidden Physics.
CoRR
Lu Zhang, Huaiqian You, Tian Gao, Mo Yu, Chung-Hao Lee, Yue Yu
2022 A* conf
IDYNO: Learning Nonparametric DAGs from Interventional Dynamic Data.
ICML
Tian Gao, Debarun Bhattacharjya, Elliot Nelson, Miao Liu, Yue Yu
2022 A conf
Linearizing contextual bandits with latent state dynamics.
UAI
Elliot Nelson, Debarun Bhattacharjya, Tian Gao, Miao Liu, Djallel Bouneffouf, Pascal Poupart
2022 J jnl
Nonlocal Kernel Network (NKN): a Stable and Resolution-Independent Deep Neural Network.
CoRR
Huaiqian You, Yue Yu, Marta D'Elia, Tian Gao, Stewart Silling
2022 J jnl
Nonlocal kernel network (NKN): A stable and resolution-independent deep neural network.
J. Comput. Phys.
Huaiqian You, Yue Yu, Marta D'Elia, Tian Gao, Stewart Silling
2021 A* conf
DAGs with No Curl: An Efficient DAG Structure Learning Approach.
ICML
Yue Yu, Tian Gao, Naiyu Yin, Qiang Ji
2021 J jnl
DAGs with No Curl: An Efficient DAG Structure Learning Approach.
CoRR
Yue Yu, Tian Gao, Naiyu Yin, Qiang Ji
2021 — conf
Timeline Summarization based on Event Graph Compression via Time-Aware Optimal Transport.
EMNLP (1)
Manling Li, Tengfei Ma, Mo Yu, Lingfei Wu, Tian Gao, Heng Ji, Kathleen R. McKeown
2020 A* conf
DAGs with No Fears: A Closer Look at Continuous Optimization for Learning Bayesian Networks.
NeurIPS
Dennis Wei, Tian Gao, Yue Yu
2020 J jnl
DAGs with No Fears: A Closer Look at Continuous Optimization for Learning Bayesian Networks.
CoRR
Dennis Wei, Tian Gao, Yue Yu
2020 — conf
MCMH: Learning Multi-Chain Multi-Hop Rules for Knowledge Graph Reasoning.
EMNLP (Findings)
Lu Zhang, Mo Yu, Tian Gao, Yue Yu
2020 J jnl
MCMH: Learning Multi-Chain Multi-Hop Rules for Knowledge Graph Reasoning.
CoRR
Lu Zhang, Mo Yu, Tian Gao, Yue Yu
2019 A* conf
A Sequential Set Generation Method for Predicting Set-Valued Outputs.
AAAI
Tian Gao, Jie Chen, Vijil Chenthamarakshan, Michael Witbrock
2019 J jnl
A Sequential Set Generation Method for Predicting Set-Valued Outputs.
CoRR
Tian Gao, Jie Chen, Vijil Chenthamarakshan, Michael Witbrock
2019 A* conf
DAG-GNN: DAG Structure Learning with Graph Neural Networks.
ICML
Yue Yu, Jie Chen, Tian Gao, Mo Yu
2019 J jnl
DAG-GNN: DAG Structure Learning with Graph Neural Networks.
CoRR
Yue Yu, Jie Chen, Tian Gao, Mo Yu
2019 — conf
Do Multi-hop Readers Dream of Reasoning Chains?
MRQA@EMNLP
Haoyu Wang, Mo Yu, Xiaoxiao Guo, Rajarshi Das, Wenhan Xiong, Tian Gao
2019 J jnl
Do Multi-hop Readers Dream of Reasoning Chains?
CoRR
Haoyu Wang, Mo Yu, Xiaoxiao Guo, Rajarshi Das, Wenhan Xiong, Tian Gao
2019 — conf
Multi-step Entity-centric Information Retrieval for Multi-Hop Question Answering.
MRQA@EMNLP
Rajarshi Das, Ameya Godbole, Dilip Kavarthapu, Zhiyu Gong, Abhishek Singhal, Mo Yu, Xiaoxiao Guo, Tian Gao, Hamed Zamani, Manzil Zaheer, Andrew McCallum
2019 J jnl
Multi-step Entity-centric Information Retrieval for Multi-Hop Question Answering.
CoRR
Ameya Godbole, Dilip Kavarthapu, Rajarshi Das, Zhiyu Gong, Abhishek Singhal, Hamed Zamani, Mo Yu, Tian Gao, Xiaoxiao Guo, Manzil Zaheer, Andrew McCallum
2019 — conf
PEARL: Prototype Learning via Rule Learning.
BCB
Tianfan Fu, Tian Gao, Cao Xiao, Tengfei Ma, Jimeng Sun
2019 — conf
PEARL: Prototype Learning via Rule Learning.
BCB
Tianfan Fu, Tian Gao, Cao Xiao, Tengfei Ma, Jimeng Sun