Articles with public access mandates - Tahrima RahmanLearn more
Available somewhere: 14
Anchoring bias affects mental model formation and user reliance in explainable AI systems
M Nourani, C Roy, JE Block, DR Honeycutt, T Rahman, E Ragan, ...
Proceedings of the 26th International Conference on Intelligent User …, 2021
Mandates: US National Science Foundation, US Department of Defense
Merging Strategies for Sum-Product Networks: From Trees to Graphs.
T Rahman, V Gogate
UAI, 2016
Mandates: US National Science Foundation
Explainable activity recognition in videos: Lessons learned
C Roy, M Nourani, DR Honeycutt, JE Block, T Rahman, ED Ragan, ...
Applied AI Letters 2 (4), e59, 2021
Mandates: US National Science Foundation, US Department of Defense
Cutset Bayesian Networks: A New Representation for Learning Rao-Blackwellised Graphical Models
T Rahman, S Jin, V Gogate
Proceedings of the Twenty-Eighth International Joint Conference on …, 2019
Mandates: US National Science Foundation, US Department of Defense
Look ma, no latent variables: Accurate cutset networks via compilation
T Rahman, S Jin, V Gogate
International Conference on Machine Learning, 5311-5320, 2019
Mandates: US National Science Foundation, US Department of Defense
Algorithms for the Nearest Assignment Problem.
S Rouhani, T Rahman, V Gogate
IJCAI, 5096-5102, 2018
Mandates: US National Science Foundation, US Department of Defense
On the importance of user backgrounds and impressions: Lessons learned from interactive AI applications
M Nourani, C Roy, JE Block, DR Honeycutt, T Rahman, ED Ragan, ...
ACM Transactions on Interactive Intelligent Systems 12 (4), 1-29, 2022
Mandates: US National Science Foundation, US Department of Defense
A novel approach for constrained optimization in graphical models
S Rouhani, T Rahman, V Gogate
Advances in Neural Information Processing Systems 33, 11949-11960, 2020
Mandates: US National Science Foundation, US Department of Defense
Novel upper bounds for the constrained most probable explanation task
T Rahman, S Rouhani, V Gogate
Advances in Neural Information Processing Systems 34, 9613-9624, 2021
Mandates: US National Science Foundation, US Department of Defense
Dynamic cutset networks
C Roy, T Rahman, H Dong, N Ruozzi, V Gogate
International Conference on Artificial Intelligence and Statistics, 3106-3114, 2021
Mandates: US National Science Foundation, US Department of Defense
Robust learning of tractable probabilistic models
R Peddi, T Rahman, V Gogate
Uncertainty in Artificial Intelligence, 1572-1581, 2022
Mandates: US National Science Foundation, US Department of Defense
Conditionally tractable density estimation using neural networks
H Dong, C Roy, T Rahman, V Gogate, N Ruozzi
International Conference on Artificial Intelligence and Statistics, 6933-6946, 2022
Mandates: US National Science Foundation, US Department of Defense
Learning tractable probabilistic models from inconsistent local estimates
S Jin, V Komaragiri, T Rahman, V Gogate
Advances in Neural Information Processing Systems 35, 10367-10379, 2022
Mandates: US National Science Foundation, US Department of Defense
Deciphering a Deep Learning Black-Box via a Cutset Network: Explainable Activity Recognition in Videos
C ROY, M NOURANI, M SHANBHAG, T RAHMAN, ED RAGAN, N RUOZZI, ...
Mandates: US National Science Foundation, US Department of Defense
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