Saeedi, Ardavan

11 publications

MLHC 2025 Switching State Space Modeling via Constrained Inference for Clinical Outcome Prediction Arnold Su, Anna Wong, Fareed Sheriff, Ardavan Saeedi, Li-wei H. Lehman

AAAI 2022 Knowledge Distillation via Constrained Variational Inference Ardavan Saeedi, Yuria Utsumi, Li Sun, Kayhan Batmanghelich, Li-Wei H. Lehman

NeurIPSW 2022 Treatment-RSPN: Recurrent Sum-Product Networks for Sequential Treatment Regimes Adam Dejl, Harsh Deep, Jonathan Fei, Ardavan Saeedi, Li-wei H. Lehman

ICLR 2020 Discrepancy Ratio: Evaluating Model Performance When Even Experts Disagree on the Truth Igor Lovchinsky, Alon Daks, Israel Malkin, Pouya Samangouei, Ardavan Saeedi, Yang Liu, Swami Sankaranarayanan, Tomer Gafner, Ben Sternlieb, Patrick Maher, Nathan Silberman

ECCV 2018 ExplainGAN: Model Explanation via Decision Boundary Crossing Transformations Pouya Samangouei, Ardavan Saeedi, Liam Nakagawa, Nathan Silberman

AISTATS 2018 Multimodal Prediction and Personalization of Photo Edits with Deep Generative Models Ardavan Saeedi, Matthew D. Hoffman, Stephen J. DiVerdi, Asma Ghandeharioun, Matthew J. Johnson, Ryan P. Adams

JMLR 2017 Variational Particle Approximations Ardavan Saeedi, Tejas D. Kulkarni, Vikash K. Mansinghka, Samuel J. Gershman

NeurIPS 2016 Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation Tejas D Kulkarni, Karthik Narasimhan, Ardavan Saeedi, Josh Tenenbaum

ICML 2016 The Segmented iHMM: A Simple, Efficient Hierarchical Infinite HMM Ardavan Saeedi, Matthew Hoffman, Matthew Johnson, Ryan Adams

ICML 2015 JUMP-Means: Small-Variance Asymptotics for Markov Jump Processes Jonathan Huggins, Karthik Narasimhan, Ardavan Saeedi, Vikash Mansinghka

NeurIPS 2011 Priors over Recurrent Continuous Time Processes Ardavan Saeedi, Alexandre Bouchard-côté