Chaudhari, Pratik

38 publications

ICLR 2025 AgentOccam: A Simple yet Strong Baseline for LLM-Based Web Agents Ke Yang, Yao Liu, Sapana Chaudhary, Rasool Fakoor, Pratik Chaudhari, George Karypis, Huzefa Rangwala

TMLR 2025 Bridging the Training-Inference Gap in LLMs by Leveraging Self-Generated Tokens Zhepeng Cen, Yao Liu, Siliang Zeng, Pratik Chaudhari, Huzefa Rangwala, George Karypis, Rasool Fakoor

ICLRW 2025 Bridging the Training-Inference Gap in LLMs by Leveraging Self-Generated Tokens Zhepeng Cen, Yao Liu, Siliang Zeng, Pratik Chaudhari, Huzefa Rangwala, George Karypis, Rasool Fakoor

ICCV 2025 From Linearity to Non-Linearity: How Masked Autoencoders Capture Spatial Correlations Anthony Bisulco, Rahul Ramesh, Randall Balestriero, Pratik Chaudhari

ICLRW 2025 Observability of Latent States in Generative AI Models Tian Yu Liu, Stefano Soatto, Matteo Marchi, Pratik Chaudhari, Paulo Tabuada

NeurIPS 2025 REMI: Reconstructing Episodic Memory During Internally Driven Path Planning Zhaoze Wang, Genela Morris, Dori Derdikman, Pratik Chaudhari, Vijay Balasubramanian

NeurIPS 2024 Deep Learning in Medical Image Registration: Magic or Mirage? Rohit Jena, Deeksha Sethi, Pratik Chaudhari, James C. Gee

NeurIPS 2024 Prospective Learning: Learning for a Dynamic Future Ashwin De Silva, Rahul Ramesh, Rubing Yang, Siyu Yu, Joshua T. Vogelstein, Pratik Chaudhari

NeurIPSW 2024 Prospective Learning: Learning for a Dynamic Future Ashwin De Silva, Rahul Ramesh, Rubing Yang, Siyu Yu, Joshua T Vogelstein, Pratik Chaudhari

ICLR 2024 Time-Varying Propensity Score to Bridge the Gap Between the past and Present Rasool Fakoor, Jonas Mueller, Zachary Chase Lipton, Pratik Chaudhari, Alex Smola

NeurIPSW 2024 dSTAR: Straggler Tolerant and Byzantine Resilient Distributed SGD Jiahe Yan, Pratik Chaudhari, Leonard Kleinrock

ICML 2023 A Picture of the Space of Typical Learnable Tasks Rahul Ramesh, Jialin Mao, Itay Griniasty, Rubing Yang, Han Kheng Teoh, Mark Transtrum, James Sethna, Pratik Chaudhari

CVPR 2023 Beyond mAP: Towards Better Evaluation of Instance Segmentation Rohit Jena, Lukas Zhornyak, Nehal Doiphode, Pratik Chaudhari, Vivek Buch, James Gee, Jianbo Shi

NeurIPS 2023 Budgeting Counterfactual for Offline RL Yao Liu, Pratik Chaudhari, Rasool Fakoor

NeurIPSW 2023 Investigating Causality Between Genotype and Clinical Phenotype in Neurological Disorders Using Structural Causal Model and Normalizing Flow Fanyang Yu, Rongguang Wang, Pratik Chaudhari, Christos Davatzikos

CoLLAs 2023 Prospective Learning: Principled Extrapolation to the Future Ashwin De Silva, Rahul Ramesh, Lyle Ungar, Marshall Hussain Shuler, Noah J. Cowan, Michael Platt, Chen Li, Leyla Isik, Seung-Eon Roh, Adam Charles, Archana Venkataraman, Brian Caffo, Javier J. How, Justus M Kebschull, John W. Krakauer, Maxim Bichuch, Kaleab Alemayehu Kinfu, Eva Yezerets, Dinesh Jayaraman, Jong M. Shin, Soledad Villar, Ian Phillips, Carey E. Priebe, Thomas Hartung, Michael I. Miller, Jayanta Dey, Ningyuan Huang, Eric Eaton, Ralph Etienne-Cummings, Elizabeth L. Ogburn, Randal Burns, Onyema Osuagwu, Brett Mensh, Alysson R. Muotri, Julia Brown, Chris White, Weiwei Yang, Andrei A. Rusu Timothy Verstynen, Konrad P. Kording, Pratik Chaudhari, Joshua T. Vogelstein

ECML-PKDD 2023 Sparse Neural Additive Model: Interpretable Deep Learning with Feature Selection via Group Sparsity Shiyun Xu, Zhiqi Bu, Pratik Chaudhari, Ian J. Barnett

ICML 2023 The Value of Out-of-Distribution Data Ashwin De Silva, Rahul Ramesh, Carey Priebe, Pratik Chaudhari, Joshua T Vogelstein

ICML 2022 Deep Reference Priors: What Is the Best Way to Pretrain a Model? Yansong Gao, Rahul Ramesh, Pratik Chaudhari

ICML 2022 Does the Data Induce Capacity Control in Deep Learning? Rubing Yang, Jialin Mao, Pratik Chaudhari

AAAI 2022 Does the Geometry of the Data Control the Geometry of Neural Predictions? (Student Abstract) Anirudh Cowlagi, Pratik Chaudhari

ICLR 2022 Model Zoo: A Growing Brain That Learns Continually Rahul Ramesh, Pratik Chaudhari

ICLRW 2022 Sparse Neural Additive Model: Interpretable Deep Learning with Feature Selection via Group Sparsity Shiyun Xu, Zhiqi Bu, Pratik Chaudhari, Ian J. Barnett

NeurIPSW 2022 The Value of Out-of-Distribution Data Ashwin De Silva, Rahul Ramesh, Carey Priebe, Pratik Chaudhari, Joshua T Vogelstein

ICML 2021 An Information-Geometric Distance on the Space of Tasks Yansong Gao, Pratik Chaudhari

NeurIPS 2021 Continuous Doubly Constrained Batch Reinforcement Learning Rasool Fakoor, Jonas W Mueller, Kavosh Asadi, Pratik Chaudhari, Alexander J Smola

NeurIPSW 2021 Model Zoo: A Growing Brain That Learns Continually Rahul Ramesh, Pratik Chaudhari

ICLR 2020 A Baseline for Few-Shot Image Classification Guneet S. Dhillon, Pratik Chaudhari, Avinash Ravichandran, Stefano Soatto

ICML 2020 A Free-Energy Principle for Representation Learning Yansong Gao, Pratik Chaudhari

ICLRW 2020 A Free-Energy Principle for Representation Learning Yansong Gao, Pratik Chaudhari

CoRL 2020 BayesRace: Learning to Race Autonomously Using Prior Experience Achin Jain, Matthew O’Kelly, Pratik Chaudhari, Manfred Morari

NeurIPS 2020 Fast, Accurate, and Simple Models for Tabular Data via Augmented Distillation Rasool Fakoor, Jonas W Mueller, Nick Erickson, Pratik Chaudhari, Alexander J Smola

ICLR 2020 Meta-Q-Learning Rasool Fakoor, Pratik Chaudhari, Stefano Soatto, Alexander J. Smola

ICLR 2020 Rethinking the Hyperparameters for Fine-Tuning Hao Li, Pratik Chaudhari, Hao Yang, Michael Lam, Avinash Ravichandran, Rahul Bhotika, Stefano Soatto

UAI 2019 P3O: Policy-on Policy-Off Policy Optimization Rasool Fakoor, Pratik Chaudhari, Alexander J. Smola

ICMLW 2019 P3O: Policy-on Policy-Off Policy Optimization Rasool Fakoor, Pratik Chaudhari, Alexander J. Smola

ICLR 2018 Stochastic Gradient Descent Performs Variational Inference, Converges to Limit Cycles for Deep Networks Pratik Chaudhari, Stefano Soatto

ICLR 2017 Entropy-SGD: Biasing Gradient Descent into Wide Valleys Pratik Chaudhari, Anna Choromanska, Stefano Soatto, Yann LeCun, Carlo Baldassi, Christian Borgs, Jennifer T. Chayes, Levent Sagun, Riccardo Zecchina