Ardavan Saeedi

31 papers A* 6A 1Journal 15Unranked 8

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Generative Active Testing: Efficient LLM Evaluation via Proxy Task Adaptation. CoRR Aashish Anantha Ramakrishnan, Ardavan Saeedi, Hamid Reza Hassanzadeh, Fazlolah Mohaghegh, Dongwon Lee
2025	A*	`conf`	LLMs are Better Than You Think: Label-Guided In-Context Learning for Named Entity Recognition. EMNLP Fan Bai, Hamid Hassanzadeh, Ardavan Saeedi, Mark Dredze
2025	J	`jnl`	Label-Guided In-Context Learning for Named Entity Recognition. CoRR Fan Bai, Hamid Hassanzadeh, Ardavan Saeedi, Mark Dredze
2025	—	`conf`	Switching State Space Modeling via Constrained Inference for Clinical Outcome Prediction. MLHC Arnold Su, Anna Wong, Fareed Sheriff, Ardavan Saeedi, Li-Wei H. Lehman
2024	J	`jnl`	Give me Some Hard Questions: Synthetic Data Generation for Clinical QA. CoRR Fan Bai, Keith Harrigian, Joel Stremmel, Hamid Hassanzadeh, Ardavan Saeedi, Mark Dredze
2023	J	`jnl`	A Knowledge Distillation Approach for Sepsis Outcome Prediction from Multivariate Clinical Time Series. CoRR Anna Wong, Shu Ge, Nassim Oufattole, Adam Dejl, Megan Su, Ardavan Saeedi, Li-Wei H. Lehman
2023	J	`jnl`	XAIQA: Explainer-Based Data Augmentation for Extractive Question Answering. CoRR Joel Stremmel, Ardavan Saeedi, Hamid Hassanzadeh, Sanjit S. Batra, Jeffrey Hertzberg, Jaime Murillo, Eran Halperin
2022	A*	`conf`	Knowledge Distillation via Constrained Variational Inference. AAAI Ardavan Saeedi, Yuria Utsumi, Li Sun, Kayhan Batmanghelich, Li-Wei H. Lehman
2022	J	`jnl`	Treatment-RSPN: Recurrent Sum-Product Networks for Sequential Treatment Regimes. CoRR Adam Dejl, Harsh Deep, Jonathan Fei, Ardavan Saeedi, Li-Wei H. Lehman
2021	—	`conf`	Incorporating External Information in Tissue Subtyping: A Topic Modeling Approach. MLHC Ardavan Saeedi, Payman Yadollahpour, Sumedha Singla, Brian Pollack, William M. Wells III, Frank C. Sciurba, Kayhan Batmanghelich
2020	A*	`conf`	Discrepancy Ratio: Evaluating Model Performance When Even Experts Disagree on the Truth. ICLR Igor Lovchinsky, Alon Daks, Israel Malkin, Pouya Samangouei, Ardavan Saeedi, Yang Liu, Swami Sankaranarayanan, Tomer Gafner, Ben Sternlieb, Patrick Maher, Nathan Silberman
2019	J	`jnl`	Learning From Noisy Labels By Regularized Estimation Of Annotator Confusion. CoRR Ryutaro Tanno, Ardavan Saeedi, Swami Sankaranarayanan, Daniel C. Alexander, Nathan Silberman
2019	A*	`conf`	Learning From Noisy Labels by Regularized Estimation of Annotator Confusion. CVPR Ryutaro Tanno, Ardavan Saeedi, Swami Sankaranarayanan, Daniel C. Alexander, Nathan Silberman
2018	—	`conf`	ExplainGAN: Model Explanation via Decision Boundary Crossing Transformations. ECCV (10) Pouya Samangouei, Ardavan Saeedi, Liam Nakagawa, Nathan Silberman
2018	—	`—`	Latent variable models for understanding user behavior in software applications. Ardavan Saeedi
2018	A	`conf`	Multimodal Prediction and Personalization of Photo Edits with Deep Generative Models. AISTATS Ardavan Saeedi, Matthew D. Hoffman, Stephen J. DiVerdi, Asma Ghandeharioun, Matthew J. Johnson, Ryan P. Adams
2017	J	`jnl`	Multimodal Prediction and Personalization of Photo Edits with Deep Generative Models. CoRR Ardavan Saeedi, Matthew D. Hoffman, Stephen J. DiVerdi, Asma Ghandeharioun, Matthew J. Johnson, Ryan P. Adams
2017	J	`jnl`	Variational Particle Approximations. J. Mach. Learn. Res. Ardavan Saeedi, Tejas D. Kulkarni, Vikash K. Mansinghka, Samuel J. Gershman
2016	J	`jnl`	Deep Successor Reinforcement Learning. CoRR Tejas D. Kulkarni, Ardavan Saeedi, Simanta Gautam, Samuel J. Gershman
2016	—	`conf`	Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation. NIPS Tejas D. Kulkarni, Karthik Narasimhan, Ardavan Saeedi, Josh Tenenbaum
2016	J	`jnl`	Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation. CoRR Tejas D. Kulkarni, Karthik Narasimhan, Ardavan Saeedi, Joshua B. Tenenbaum
2016	—	`conf`	Inferring Disease Status by Non-parametric Probabilistic Embedding. MCV/BAMBI@MICCAI Nematollah Kayhan Batmanghelich, Ardavan Saeedi, Raúl San José Estépar, Michael H. Cho, William M. Wells III
2016	—	`conf`	Nonparametric Spherical Topic Modeling with Word Embeddings. ACL (2) Kayhan N. Batmanghelich, Ardavan Saeedi, Karthik Narasimhan, Samuel Gershman
2016	J	`jnl`	Nonparametric Spherical Topic Modeling with Word Embeddings. CoRR Kayhan N. Batmanghelich, Ardavan Saeedi, Karthik Narasimhan, Samuel Gershman
2016	A*	`conf`	The Segmented iHMM: A Simple, Efficient Hierarchical Infinite HMM. ICML Ardavan Saeedi, Matthew D. Hoffman, Matthew J. Johnson, Ryan P. Adams
2015	J	`jnl`	Detailed Derivations of Small-Variance Asymptotics for some Hierarchical Bayesian Nonparametric Models. CoRR Jonathan H. Huggins, Ardavan Saeedi, Matthew J. Johnson
2015	—	`conf`	Generative Method to Discover Genetically Driven Image Biomarkers. IPMI Nematollah Kayhan Batmanghelich, Ardavan Saeedi, Michael H. Cho, Raúl San José Estépar, Polina Golland
2015	A*	`conf`	JUMP-Means: Small-Variance Asymptotics for Markov Jump Processes. ICML Jonathan H. Huggins, Karthik Narasimhan, Ardavan Saeedi, Vikash Mansinghka
2015	J	`jnl`	JUMP-Means: Small-Variance Asymptotics for Markov Jump Processes. CoRR Jonathan H. Huggins, Karthik Narasimhan, Ardavan Saeedi, Vikash K. Mansinghka
2014	J	`jnl`	Variational Particle Approximations. CoRR Tejas D. Kulkarni, Ardavan Saeedi, Samuel Gershman
2011	—	`conf`	Priors over Recurrent Continuous Time Processes. NIPS Ardavan Saeedi, Alexandre Bouchard-Côté