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ORCIDTian Gao 0007
Person information
- affiliation: IBM Research, Yorktown Heights, NY, USA
Other persons with the same name
- Tian Gao — disambiguation page
- Tian Gao 0001
![[0000-0001-9261-826X]](https://dblp.org/img/orcid-mark.12x12.png "0000-0001-9261-826X")
— Inner Mongolia Agricultural University, Hohhot, China - Tian Gao 0002 — University of Nebraska-Lincoln, Lincoln, NE, USA
- Tian Gao 0003 — IBM T. J. Watson Research Center, Yorktown Heights, NY, USA
- Tian Gao 0004 — Nanjing University of Science and Technology, Nanjing, Jiangsu, China
- Tian Gao 0005 — IFlyTek, Hefei, China (and 1 more)
- Tian Gao 0006 — Information Engineering University, Zhengzhou, China
Other persons with a similar name
- Harry Gao (aka: Harry Tian Gao)
- Ling-Tian Gao
- Tian-Fu Gao
- Tian-yi Gao
- Tian Yang Gao
- Tianhan Gao (aka: Tian-han Gao) — Northeastern University, Software College, Shenyang, China
- Xiao-Tian Gao
- Yi-Tian Gao
- Yan Gao-Tian
- Gao Tian
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2020 – today
- 2026
[i17]Naiyu Yin, Dennis Wei, Tian Gao, Amit Dhurandhar, Karthikeyan Natesan Ramamurthy, Yue Yu:
Scalable Circuit Learning for Interpreting Large Language Models. CoRR abs/2606.16939 (2026)- 2025
- [c18]Junkyu Lee, Tian Gao, Elliot Nelson, Miao Liu, Debarun Bhattacharjya, Songtao Lu:
Q-function Decomposition with Intervention Semantics for Factored Action Spaces. AISTATS 2025: 1027-1035 - [c17]Tian Gao, Songtao Lu, Junkyu Lee, Elliot Nelson, Debarun Bhattacharjya, Yue Yu, Miao Liu:
Meta-D2AG: Causal Graph Learning with Interventional Dynamic Data. NeurIPS 2025 - [i16]Junkyu Lee, Tian Gao, Elliot Nelson, Miao Liu, Debarun Bhattacharjya, Songtao Lu:
Q-function Decomposition with Intervention Semantics with Factored Action Spaces. CoRR abs/2504.21326 (2025) - [i15]Naiyu Yin, Tian Gao, Yue Yu:
Learning Causal Graphs at Scale: A Foundation Model Approach. CoRR abs/2506.18285 (2025) - [i14]Haotian Xu, Tian Gao, Tsui-Wei Weng, Tengfei Ma:
Resting Neurons, Active Insights: Improving Input Sparsification for Large Language Models. CoRR abs/2512.12744 (2025) - 2024
- [c16]Naiyu Yin, Tian Gao, Yue Yu, Qiang Ji:
Effective Causal Discovery under Identifiable Heteroscedastic Noise Model. AAAI 2024: 16486-16494 - [c15]Naiyu Yin, Hanjing Wang, Yue Yu, Tian Gao, Amit Dhurandhar, Qiang Ji:
Integrating Markov Blanket Discovery Into Causal Representation Learning for Domain Generalization. ECCV (10) 2024: 271-288 - [c14]Naiyu Yin, Yue Yu, Tian Gao, Qiang Ji:
Efficient Nonlinear DAG Learning Under Projection Framework. ICPR (6) 2024: 445-460 - [c13]Yue Yu, Ning Liu, Fei Lu, Tian Gao, Siavash Jafarzadeh, Stewart A. Silling:
Nonlocal Attention Operator: Materializing Hidden Knowledge Towards Interpretable Physics Discovery. NeurIPS 2024 - [i13]Yue Yu, Ning Liu, Fei Lu, Tian Gao, Siavash Jafarzadeh, Stewart Silling:
Nonlocal Attention Operator: Materializing Hidden Knowledge Towards Interpretable Physics Discovery. CoRR abs/2408.07307 (2024) - [i12]Ning Liu, Lu Zhang, Tian Gao, Yue Yu:
Disentangled Representation Learning for Parametric Partial Differential Equations. CoRR abs/2410.02136 (2024) - [i11]Tian Gao, Amit Dhurandhar, Karthikeyan Natesan Ramamurthy, Dennis Wei:
Identifying Sub-networks in Neural Networks via Functionally Similar Representations. CoRR abs/2410.16484 (2024) - 2023
- [i10]Lu Zhang, Huaiqian You, Tian Gao, Mo Yu, Chung-Hao Lee, Yue Yu:
MetaNO: How to Transfer Your Knowledge on Learning Hidden Physics. CoRR abs/2301.12095 (2023) - [i9]Naiyu Yin, Tian Gao, Yue Yu, Qiang Ji:
Causal Discovery under Identifiable Heteroscedastic Noise Model. CoRR abs/2312.12844 (2023) - 2022
- [j1]Huaiqian You, Yue Yu, Marta D'Elia, Tian Gao, Stewart Silling:
Nonlocal kernel network (NKN): A stable and resolution-independent deep neural network. J. Comput. Phys. 469: 111536 (2022) - [c12]Tian Gao, Debarun Bhattacharjya, Elliot Nelson, Miao Liu, Yue Yu:
IDYNO: Learning Nonparametric DAGs from Interventional Dynamic Data. ICML 2022: 6988-7001 - [c11]Elliot Nelson, Debarun Bhattacharjya, Tian Gao, Miao Liu, Djallel Bouneffouf, Pascal Poupart:
Linearizing contextual bandits with latent state dynamics. UAI 2022: 1477-1487 - [i8]Huaiqian You, Yue Yu, Marta D'Elia, Tian Gao, Stewart Silling:
Nonlocal Kernel Network (NKN): a Stable and Resolution-Independent Deep Neural Network. CoRR abs/2201.02217 (2022) - 2021
- [c10]Manling Li, Tengfei Ma, Mo Yu, Lingfei Wu, Tian Gao, Heng Ji, Kathleen R. McKeown:
Timeline Summarization based on Event Graph Compression via Time-Aware Optimal Transport. EMNLP (1) 2021: 6443-6456 - [c9]Yue Yu, Tian Gao, Naiyu Yin, Qiang Ji:
DAGs with No Curl: An Efficient DAG Structure Learning Approach. ICML 2021: 12156-12166 - [i7]Yue Yu, Tian Gao, Naiyu Yin, Qiang Ji:
DAGs with No Curl: An Efficient DAG Structure Learning Approach. CoRR abs/2106.07197 (2021) - 2020
- [c8]Lu Zhang, Mo Yu, Tian Gao, Yue Yu:
MCMH: Learning Multi-Chain Multi-Hop Rules for Knowledge Graph Reasoning. EMNLP (Findings) 2020: 3948-3954 - [c7]Dennis Wei, Tian Gao, Yue Yu:
DAGs with No Fears: A Closer Look at Continuous Optimization for Learning Bayesian Networks. NeurIPS 2020 - [i6]Lu Zhang, Mo Yu, Tian Gao, Yue Yu:
MCMH: Learning Multi-Chain Multi-Hop Rules for Knowledge Graph Reasoning. CoRR abs/2010.01735 (2020) - [i5]Dennis Wei, Tian Gao, Yue Yu:
DAGs with No Fears: A Closer Look at Continuous Optimization for Learning Bayesian Networks. CoRR abs/2010.09133 (2020)
2010 – 2019
- 2019
- [c6]Tian Gao, Jie Chen, Vijil Chenthamarakshan, Michael Witbrock:
A Sequential Set Generation Method for Predicting Set-Valued Outputs. AAAI 2019: 2835-2842 - [c5]Haoyu Wang, Mo Yu, Xiaoxiao Guo, Rajarshi Das, Wenhan Xiong, Tian Gao:
Do Multi-hop Readers Dream of Reasoning Chains? MRQA@EMNLP 2019: 91-97 - [c4]Rajarshi Das, Ameya Godbole, Dilip Kavarthapu, Zhiyu Gong, Abhishek Singhal, Mo Yu, Xiaoxiao Guo, Tian Gao, Hamed Zamani, Manzil Zaheer, Andrew McCallum:
Multi-step Entity-centric Information Retrieval for Multi-Hop Question Answering. MRQA@EMNLP 2019: 113-118 - [c3]Tianfan Fu, Tian Gao, Cao Xiao, Tengfei Ma, Jimeng Sun:
PEARL: Prototype Learning via Rule Learning. BCB 2019: 223-232 - [c2]Tianfan Fu, Tian Gao, Cao Xiao, Tengfei Ma, Jimeng Sun:
PEARL: Prototype Learning via Rule Learning. BCB 2019: 542 - [c1]Yue Yu, Jie Chen, Tian Gao, Mo Yu:
DAG-GNN: DAG Structure Learning with Graph Neural Networks. ICML 2019: 7154-7163 - [i4]Tian Gao, Jie Chen, Vijil Chenthamarakshan, Michael Witbrock:
A Sequential Set Generation Method for Predicting Set-Valued Outputs. CoRR abs/1903.05153 (2019) - [i3]Yue Yu, Jie Chen, Tian Gao, Mo Yu:
DAG-GNN: DAG Structure Learning with Graph Neural Networks. CoRR abs/1904.10098 (2019) - [i2]Ameya Godbole, Dilip Kavarthapu, Rajarshi Das, Zhiyu Gong, Abhishek Singhal, Hamed Zamani, Mo Yu, Tian Gao, Xiaoxiao Guo, Manzil Zaheer, Andrew McCallum:
Multi-step Entity-centric Information Retrieval for Multi-Hop Question Answering. CoRR abs/1909.07598 (2019) - [i1]Haoyu Wang, Mo Yu, Xiaoxiao Guo, Rajarshi Das, Wenhan Xiong, Tian Gao:
Do Multi-hop Readers Dream of Reasoning Chains? CoRR abs/1910.14520 (2019)
Coauthor Index
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