Ardavan Saeedi

According to our database, Ardavan Saeedi authored at least 21 papers between 2011 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

XAIQA: Explainer-Based Data Augmentation for Extractive Question Answering.

Joel Stremmel, Ardavan Saeedi, Hamid Hassanzadeh, Sanjit S. Batra, Jeffrey Hertzberg, Jaime Murillo, Eran Halperin

CoRR, 2023

A Knowledge Distillation Approach for Sepsis Outcome Prediction from Multivariate Clinical Time Series.

Anna Wong, Shu Ge, Nassim Oufattole, Adam Dejl, Megan Su, Ardavan Saeedi, Li-Wei H. Lehman

CoRR, 2023

2022

Treatment-RSPN: Recurrent Sum-Product Networks for Sequential Treatment Regimes.

Adam Dejl, Harsh Deep, Jonathan Fei, Ardavan Saeedi, Li-Wei H. Lehman

CoRR, 2022

Knowledge Distillation via Constrained Variational Inference.

Ardavan Saeedi, Yuria Utsumi, Li Sun, Kayhan Batmanghelich, Li-Wei H. Lehman

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Incorporating External Information in Tissue Subtyping: A Topic Modeling Approach.

Ardavan Saeedi, Payman Yadollahpour, Sumedha Singla, Brian Pollack, William M. Wells III, Frank C. Sciurba, Kayhan Batmanghelich

Proceedings of the Machine Learning for Healthcare Conference, 2021

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

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Learning From Noisy Labels by Regularized Estimation of Annotator Confusion.

Ryutaro Tanno, Ardavan Saeedi, Swami Sankaranarayanan, Daniel C. Alexander, Nathan Silberman

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018

Latent variable models for understanding user behavior in software applications.

Ardavan Saeedi

PhD thesis, 2018

ExplainGAN: Model Explanation via Decision Boundary Crossing Transformations.

Pouya Samangouei, Ardavan Saeedi, Liam Nakagawa, Nathan Silberman

Proceedings of the Computer Vision - ECCV 2018, 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

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

Variational Particle Approximations.

Ardavan Saeedi, Tejas D. Kulkarni, Vikash K. Mansinghka, Samuel J. Gershman

J. Mach. Learn. Res., 2017

2016

Deep Successor Reinforcement Learning.

Tejas D. Kulkarni, Ardavan Saeedi, Simanta Gautam, Samuel J. Gershman

CoRR, 2016

Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation.

Tejas D. Kulkarni, Karthik Narasimhan, Ardavan Saeedi, Josh Tenenbaum

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Inferring Disease Status by Non-parametric Probabilistic Embedding.

Nematollah Kayhan Batmanghelich, Ardavan Saeedi, Raúl San José Estépar, Michael H. Cho, William M. Wells III

Proceedings of the Medical Computer Vision and Bayesian and Graphical Models for Biomedical Imaging, 2016

The Segmented iHMM: A Simple, Efficient Hierarchical Infinite HMM.

Ardavan Saeedi, Matthew D. Hoffman, Matthew J. Johnson, Ryan P. Adams

Proceedings of the 33nd International Conference on Machine Learning, 2016

Nonparametric Spherical Topic Modeling with Word Embeddings.

Kayhan N. Batmanghelich, Ardavan Saeedi, Karthik Narasimhan, Samuel Gershman

Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, 2016

2015

Detailed Derivations of Small-Variance Asymptotics for some Hierarchical Bayesian Nonparametric Models.

Jonathan H. Huggins, Ardavan Saeedi, Matthew J. Johnson

CoRR, 2015

Generative Method to Discover Genetically Driven Image Biomarkers.

Nematollah Kayhan Batmanghelich, Ardavan Saeedi, Michael H. Cho, Raúl San José Estépar, Polina Golland

Proceedings of the Information Processing in Medical Imaging, 2015

JUMP-Means: Small-Variance Asymptotics for Markov Jump Processes.

Jonathan H. Huggins, Karthik Narasimhan, Ardavan Saeedi, Vikash Mansinghka

Proceedings of the 32nd International Conference on Machine Learning, 2015

2014

Variational Particle Approximations.

Tejas D. Kulkarni, Ardavan Saeedi, Samuel Gershman

CoRR, 2014

2011

Priors over Recurrent Continuous Time Processes.

Ardavan Saeedi, Alexandre Bouchard-Côté

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011