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ORCIDTahrima Rahman
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2020 – today
- 2024
[c17]Shivvrat Arya
, Tahrima Rahman, Vibhav Gogate:
Neural Network Approximators for Marginal MAP in Probabilistic Circuits. AAAI 2024: 10918-10926- [c16]Shivvrat Arya, Tahrima Rahman, Vibhav Gogate:
Learning to Solve the Constrained Most Probable Explanation Task in Probabilistic Graphical Models. AISTATS 2024: 2791-2799 - [i3]Shivvrat Arya, Tahrima Rahman, Vibhav Gogate:
Neural Network Approximators for Marginal MAP in Probabilistic Circuits. CoRR abs/2402.03621 (2024) - [i2]Shivvrat Arya, Tahrima Rahman, Vibhav Gogate:
Learning to Solve the Constrained Most Probable Explanation Task in Probabilistic Graphical Models. CoRR abs/2404.11606 (2024) - 2023
- [j2]Chiradeep Roy, Mahsan Nourani, Shivvrat Arya, Mahesh Shanbhag, Tahrima Rahman, Eric D. Ragan, Nicholas Ruozzi, Vibhav Gogate:
Explainable Activity Recognition in Videos using Deep Learning and Tractable Probabilistic Models. ACM Trans. Interact. Intell. Syst. 13(4): 29:1-29:32 (2023) - 2022
- [j1]Mahsan Nourani, Chiradeep Roy, Jeremy E. Block, Donald R. Honeycutt, Tahrima Rahman, Eric D. Ragan, Vibhav Gogate:
On the Importance of User Backgrounds and Impressions: Lessons Learned from Interactive AI Applications. ACM Trans. Interact. Intell. Syst. 12(4): 28:1-28:29 (2022) - [c15]Hailiang Dong, Chiradeep Roy, Tahrima Rahman, Vibhav Gogate, Nicholas Ruozzi:
Conditionally Tractable Density Estimation using Neural Networks. AISTATS 2022: 6933-6946 - [c14]Shasha Jin, Vasundhara Komaragiri, Tahrima Rahman, Vibhav Gogate:
Learning Tractable Probabilistic Models from Inconsistent Local Estimates. NeurIPS 2022 - [c13]Rohith Peddi, Tahrima Rahman, Vibhav Gogate:
Robust learning of tractable probabilistic models. UAI 2022: 1572-1581 - 2021
- [c12]Chiradeep Roy, Tahrima Rahman, Hailiang Dong, Nicholas Ruozzi, Vibhav Gogate:
Dynamic Cutset Networks. AISTATS 2021: 3106-3114 - [c11]Mahsan Nourani, Chiradeep Roy, Jeremy E. Block, Donald R. Honeycutt, Tahrima Rahman, Eric D. Ragan, Vibhav Gogate:
Anchoring Bias Affects Mental Model Formation and User Reliance in Explainable AI Systems. IUI 2021: 340-350 - [c10]Tahrima Rahman, Sara Rouhani, Vibhav Gogate:
Novel Upper Bounds for the Constrained Most Probable Explanation Task. NeurIPS 2021: 9613-9624 - 2020
- [c9]Mahsan Nourani, Donald R. Honeycutt, Jeremy E. Block, Chiradeep Roy, Tahrima Rahman, Eric D. Ragan, Vibhav Gogate:
Investigating the Importance of First Impressions and Explainable AI with Interactive Video Analysis. CHI Extended Abstracts 2020: 1-8 - [c8]Sara Rouhani, Tahrima Rahman, Vibhav Gogate:
A Novel Approach for Constrained Optimization in Graphical Models. NeurIPS 2020 - [i1]Mahsan Nourani, Chiradeep Roy, Tahrima Rahman, Eric D. Ragan, Nicholas Ruozzi, Vibhav Gogate:
Don't Explain without Verifying Veracity: An Evaluation of Explainable AI with Video Activity Recognition. CoRR abs/2005.02335 (2020)
2010 – 2019
- 2019
- [c7]Tahrima Rahman, Shasha Jin, Vibhav Gogate:
Look Ma, No Latent Variables: Accurate Cutset Networks via Compilation. ICML 2019: 5311-5320 - [c6]Tahrima Rahman, Shasha Jin, Vibhav Gogate:
Cutset Bayesian Networks: A New Representation for Learning Rao-Blackwellised Graphical Models. IJCAI 2019: 5751-5757 - [c5]Chiradeep Roy, Mahesh Shanbhag, Mahsan Nourani, Tahrima Rahman, Samia Kabir, Vibhav Gogate, Nicholas Ruozzi, Eric D. Ragan:
Explainable Activity Recognition in Videos. IUI Workshops 2019 - 2018
- [c4]Sara Rouhani, Tahrima Rahman, Vibhav Gogate:
Algorithms for the Nearest Assignment Problem. IJCAI 2018: 5096-5102 - 2016
- [c3]Tahrima Rahman, Vibhav Gogate:
Learning Ensembles of Cutset Networks. AAAI 2016: 3301-3307 - [c2]Tahrima Rahman, Vibhav Gogate:
Merging Strategies for Sum-Product Networks: From Trees to Graphs. UAI 2016 - 2014
- [c1]Tahrima Rahman, Prasanna V. Kothalkar, Vibhav Gogate:
Cutset Networks: A Simple, Tractable, and Scalable Approach for Improving the Accuracy of Chow-Liu Trees. ECML/PKDD (2) 2014: 630-645
Coauthor Index
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