Found 34 results
Author [ Title(Asc)] Type Year
Filters: Author is Julie Shah  [Clear All Filters]
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 
Booth, S., C. Muise, and J. Shah, "Evaluating the Interpretability of the Knowledge Compilation Map: Communicating Logical Statements Effectively", International Joint Conference on Artificial Intelligence (IJCAI), Macau, China, 08/2019.
Zhou, Y., S. Booth, M. Tulio Ribeiro, and J. Shah, "Do Feature Attribution Methods Correctly Attribute Features?", Proceedings of the 36th AAAI Conference on Artificial Intelligence: AAAI, 02/2022.
Ramakrishnan, R., E. Kamar, D. Dey, J. Shah, and E. Horvitz, "Discovering Blind Spots in Reinforcement Learning", International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 07/2018.
Booth*, S., Y. Zhou*, A. Shah, and J. Shah, "Bayes-TrEx: a Bayesian Sampling Approach to Model Transparency by Example", AAAI Conference on Artificial Intelligence, 2021.
Shah, A., P. Kamath, S. Li, and J. Shah, "Bayesian Inference of Temporal Task Specifications from Demonstrations", Conference on Neural Information Processing Systems, Montreal, Canada, 2018.
Kim, J., C. Muise, A. Shah, S. Agarwal, and J. Shah, "Bayesian Inference of Linear Temporal Logic Specifications for Contrastive Explanations", International Joint Conference on Artificial Intelligence (IJCAI), Macau, China, 08/2019.
Kim, B., C. Rudin, and J. Shah, "The Bayesian Case Model: A Generative Approach for Case-Based Reasoning and Prototype Classification", Neural Information Processing Systems (NIPS), 12/2014.
Gombolay, M., R. Jensen, J. Stigile, S-H. Son, and J. Shah, "Apprenticeship Scheduling: Learning to Schedule from Human Experts", International Joint Conferences on Artificial Intelligence (IJCAI), 07/2016.