Tahrima Rahman

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 21

Top Topics

Graphical Models

Bayesian Networks

Activity Recognition

Latent Variables

Top Venues

Publications

Shivvrat Arya, Tahrima Rahman, Vibhav Gogate
Neural Network Approximators for Marginal MAP in Probabilistic Circuits. AAAI (2024)
Shivvrat Arya, Tahrima Rahman, Vibhav Gogate
Neural Network Approximators for Marginal MAP in Probabilistic Circuits. CoRR (2024)
Shivvrat Arya, Tahrima Rahman, Vibhav Gogate
Learning to Solve the Constrained Most Probable Explanation Task in Probabilistic Graphical Models. AISTATS (2024)
Shivvrat Arya, Tahrima Rahman, Vibhav Gogate
Learning to Solve the Constrained Most Probable Explanation Task in Probabilistic Graphical Models. CoRR (2024)
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) (2023)
Hailiang Dong, Chiradeep Roy, Tahrima Rahman, Vibhav Gogate, Nicholas Ruozzi
Conditionally Tractable Density Estimation using Neural Networks. AISTATS (2022)
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) (2022)
Shasha Jin, Vasundhara Komaragiri, Tahrima Rahman, Vibhav Gogate
Learning Tractable Probabilistic Models from Inconsistent Local Estimates. NeurIPS (2022)
Rohith Peddi, Tahrima Rahman, Vibhav Gogate
Robust learning of tractable probabilistic models. UAI (2022)
Chiradeep Roy, Tahrima Rahman, Hailiang Dong, Nicholas Ruozzi, Vibhav Gogate
Dynamic Cutset Networks. AISTATS (2021)
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)
Tahrima Rahman, Sara Rouhani, Vibhav Gogate
Novel Upper Bounds for the Constrained Most Probable Explanation Task. NeurIPS (2021)
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)
Sara Rouhani, Tahrima Rahman, Vibhav Gogate
A Novel Approach for Constrained Optimization in Graphical Models. NeurIPS (2020)
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 (2020)
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)
Tahrima Rahman, Shasha Jin, Vibhav Gogate
Look Ma, No Latent Variables: Accurate Cutset Networks via Compilation. ICML (2019)
Tahrima Rahman, Shasha Jin, Vibhav Gogate
Cutset Bayesian Networks: A New Representation for Learning Rao-Blackwellised Graphical Models. IJCAI (2019)
Sara Rouhani, Tahrima Rahman, Vibhav Gogate
Algorithms for the Nearest Assignment Problem. IJCAI (2018)
Tahrima Rahman, Vibhav Gogate
Merging Strategies for Sum-Product Networks: From Trees to Graphs. UAI (2016)
Tahrima Rahman, Vibhav Gogate
Learning Ensembles of Cutset Networks. AAAI (2016)
Tahrima Rahman, Prasanna Kothalkar, Vibhav Gogate
Cutset Networks: A Simple, Tractable, and Scalable Approach for Improving the Accuracy of Chow-Liu Trees. ECML/PKDD (2) (2014)