Pratik Chaudhari

ORCID

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 96

Top Venues

Publications

Matteo Marchi, Stefano Soatto, Pratik Chaudhari, Paulo Tabuada
Heat Death of Generative Models in Closed-Loop Learning. CoRR (2024)
Christopher D. Hsu, Pratik Chaudhari
Active Scout: Multi-Target Tracking Using Neural Radiance Fields in Dense Urban Environments. CoRR (2024)
Rohit Jena, Pratik Chaudhari, James C. Gee
FireANTs: Adaptive Riemannian Optimization for Multi-Scale Diffeomorphic Registration. CoRR (2024)
Yuwei Wu, Igor Spasojevic, Pratik Chaudhari, Vijay Kumar
Optimal Convex Cover as Collision-free Space Approximation for Trajectory Generation. CoRR (2024)
Siming He, Yuezhan Tao, Igor Spasojevic, Vijay Kumar, Pratik Chaudhari
An Active Perception Game for Robust Autonomous Exploration. CoRR (2024)
Rohit Jena, Pratik Chaudhari, James C. Gee
Deep Implicit Optimization for Robust and Flexible Image Registration. CoRR (2024)
Rahul Ramesh, Anthony Bisulco, Ronald W. Ditullio, Linran Wei, Vijay Balasubramanian, Kostas Daniilidis, Pratik Chaudhari
Many Perception Tasks are Highly Redundant Functions of their Input Data. CoRR (2024)
Rasool Fakoor, Jonas Mueller, Zachary Chase Lipton, Pratik Chaudhari, Alex Smola
Time-Varying Propensity Score to Bridge the Gap between the Past and Present. ICLR (2024)
Siming He, Zach Osman, Pratik Chaudhari
From NeRFs to Gaussian Splats, and Back. CoRR (2024)
Tian Yu Liu, Stefano Soatto, Matteo Marchi, Pratik Chaudhari, Paulo Tabuada
Meanings and Feelings of Large Language Models: Observability of Latent States in Generative AI. CoRR (2024)
Xu Liu, Jiuzhou Lei, Ankit Prabhu, Yuezhan Tao, Igor Spasojevic, Pratik Chaudhari, Nikolay Atanasov, Vijay Kumar
SlideSLAM: Sparse, Lightweight, Decentralized Metric-Semantic SLAM for Multi-Robot Navigation. CoRR (2024)
Derek Cheng, Fernando Cladera Ojeda, Ankit Prabhu, Xu Liu, Alan Zhu, Patrick Corey Green, Reza Ehsani, Pratik Chaudhari, Vijay Kumar
TreeScope: An Agricultural Robotics Dataset for LiDAR-Based Mapping of Trees in Forests and Orchards. ICRA (2024)
Yifei Simon Shao, Yuwei Wu, Laura Jarin-Lipschitz, Pratik Chaudhari, Vijay Kumar
Design and Evaluation of Motion Planners for Quadrotors in Environments with Varying Complexities. ICRA (2024)
Ashwin De Silva, Rahul Ramesh, Carey E. Priebe, Pratik Chaudhari, Joshua T. Vogelstein
The Value of Out-of-Distribution Data. ICML (2023)
Derek Cheng, Fernando Cladera Ojeda, Ankit Prabhu, Xu Liu, Alan Zhu, Patrick Corey Green, Reza Ehsani, Pratik Chaudhari, Vijay Kumar
TreeScope: An Agricultural Robotics Dataset for LiDAR-Based Mapping of Trees in Forests and Orchards. CoRR (2023)
Rohit Jena, Pratik Chaudhari, James C. Gee, Ganesh Iyer, Siddharth Choudhary, Brandon M. Smith
Mesh Strikes Back: Fast and Efficient Human Reconstruction from RGB videos. CoRR (2023)
Rahul Ramesh, Jialin Mao, Itay Griniasty, Rubing Yang, Han Kheng Teoh, Mark K. Transtrum, James P. Sethna, Pratik Chaudhari
A Picture of the Space of Typical Learnable Tasks. ICML (2023)
Jialin Mao, Itay Griniasty, Han Kheng Teoh, Rahul Ramesh, Rubing Yang, Mark K. Transtrum, James P. Sethna, Pratik Chaudhari
The Training Process of Many Deep Networks Explores the Same Low-Dimensional Manifold. CoRR (2023)
Yao Liu, Pratik Chaudhari, Rasool Fakoor
Budgeting Counterfactual for Offline RL. CoRR (2023)
Rongguang Wang, Güray Erus, Pratik Chaudhari, Christos Davatzikos
Adapting Machine Learning Diagnostic Models to New Populations Using a Small Amount of Data: Results from Clinical Neuroscience. CoRR (2023)
Ronald W. Ditullio, Chetan Parthiban, Eugenio Piasini, Pratik Chaudhari, Vijay Balasubramanian, Yale E. Cohen
Time as a supervisor: temporal regularity and auditory object learning. Frontiers Comput. Neurosci. 17 (2023)
Shiyun Xu, Zhiqi Bu, Pratik Chaudhari, Ian J. Barnett
Sparse Neural Additive Model: Interpretable Deep Learning with Feature Selection via Group Sparsity. ECML/PKDD (3) (2023)
Yansong Gao, Zhihong Pan, Xin Zhou, Le Kang, Pratik Chaudhari
Fast Diffusion Probabilistic Model Sampling through the lens of Backward Error Analysis. CoRR (2023)
Yao Liu, Pratik Chaudhari, Rasool Fakoor
Budgeting Counterfactual for Offline RL. NeurIPS (2023)
Daiwei Chen, Weikai Chang, Pratik Chaudhari
Learning Capacity: A Measure of the Effective Dimensionality of a Model. CoRR (2023)
Haoran Tang, Xin Zhou, Jieren Deng, Zhihong Pan, Hao Tian, Pratik Chaudhari
Retrieving Conditions from Reference Images for Diffusion Models. CoRR (2023)
Xiwen Liu, Keshava Katti, Yunfei He, Paul Jacob, Claudia Richter, Uwe Schroeder, Santosh Kurinec, Pratik Chaudhari, Deep Jariwala
Analog Content-Addressable Memory from Complementary FeFETs. CoRR (2023)
Rohit Jena, Lukas Zhornyak, Nehal Doiphode, Pratik Chaudhari, Vivek Buch, James C. Gee, Jianbo Shi
Beyond mAP: Towards Better Evaluation of Instance Segmentation. CVPR (2023)
Stefano Soatto, Paulo Tabuada, Pratik Chaudhari, Tian Yu Liu
Taming AI Bots: Controllability of Neural States in Large Language Models. CoRR (2023)
Ashwin De Silva, Rahul Ramesh, Lyle H. Ungar, Marshall G. 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 C. Burns, Onyema Osuagwu, Brett Mensh, Alysson R. Muotri, Julia Brown, Chris White, Weiwei Yang, Andrei A. Rusu, Timothy D. Verstynen, Konrad P. Kording, Pratik Chaudhari, Joshua T. Vogelstein
Prospective Learning: Principled Extrapolation to the Future. CoLLAs (2023)
Siming He, Christopher D. Hsu, Dexter Ong, Yifei Simon Shao, Pratik Chaudhari
Active Perception using Neural Radiance Fields. CoRR (2023)
Yifei Simon Shao, Yuwei Wu, Laura Jarin-Lipschitz, Pratik Chaudhari, Vijay Kumar
Design and Evaluation of Motion Planners for Quadrotors. CoRR (2023)
Rohit Jena, Ganesh Subramanian Iyer, Siddharth Choudhary, Brandon M. Smith, Pratik Chaudhari, James C. Gee
SplatArmor: Articulated Gaussian splatting for animatable humans from monocular RGB videos. CoRR (2023)
Rahul Ramesh, Pratik Chaudhari
Model Zoo: A Growing Brain That Learns Continually. ICLR (2022)
Shiyun Xu, Zhiqi Bu, Pratik Chaudhari, Ian J. Barnett
Sparse Neural Additive Model: Interpretable Deep Learning with Feature Selection via Group Sparsity. CoRR (2022)
Rubing Yang, Jialin Mao, Pratik Chaudhari
Does the Data Induce Capacity Control in Deep Learning? ICML (2022)
Yansong Gao, Rahul Ramesh, Pratik Chaudhari
Deep Reference Priors: What is the best way to pretrain a model? ICML (2022)
Anirudh Cowlagi, Pratik Chaudhari
Does the Geometry of the Data Control the Geometry of Neural Predictions? (Student Abstract). AAAI (2022)
Rongguang Wang, Pratik Chaudhari, Christos Davatzikos
Embracing the disharmony in medical imaging: A Simple and effective framework for domain adaptation. Medical Image Anal. 76 (2022)
Rasool Fakoor, Jonas Mueller, Zachary C. Lipton, Pratik Chaudhari, Alexander J. Smola
Data drift correction via time-varying importance weight estimator. CoRR (2022)
Rongguang Wang, Pratik Chaudhari, Christos Davatzikos
Machine Learning Models Are Not Necessarily Biased When Constructed Properly: Evidence from Neuroimaging Studies. CoRR (2022)
Christopher D. Hsu, Mulugeta A. Haile, Pratik Chaudhari
A Model for Perimeter-Defense Problems with Heterogeneous Teams. CoRR (2022)
Ashwin De Silva, Rahul Ramesh, Carey E. Priebe, Pratik Chaudhari, Joshua T. Vogelstein
The Value of Out-of-Distribution Data. CoRR (2022)
Keshava Katti, Ramya Muthukrishnan, Angelina Heyler, Sarthak Pati, Aprupa Alahari, Michael Sanborn, Emily F. Conant, Christopher Scott, Stacey Winham, Celine M. Vachon, Pratik Chaudhari, Despina Kontos, Spyridon Bakas
MammoDL: Mammographic Breast Density Estimation using Federated Learning. CoRR (2022)
Joshua T. Vogelstein, Timothy Verstynen, Konrad P. Kording, Leyla Isik, John W. Krakauer, Ralph Etienne-Cummings, Elizabeth L. Ogburn, Carey E. Priebe, Randal C. Burns, Kwame S. Kutten, James J. Knierim, James B. Potash, Thomas Hartung, Lena Smirnova, Paul Worley, Alena V. Savonenko, Ian Phillips, Michael I. Miller, René Vidal, Jeremias Sulam, Adam Charles, Noah J. Cowan, Maxim Bichuch, Archana Venkataraman, Chen Li, Nitish V. Thakor, Justus M. Kebschull, Marilyn S. Albert, Jinchong Xu, Marshall G. Hussain Shuler, Brian Caffo, J. Tilak Ratnanather, Ali Geisa, Seung-Eon Roh, Eva Yezerets, Meghana Madhyastha, Javier J. How, Tyler M. Tomita, Jayanta Dey, Ningyuan Huang, Jong M. Shin, Kaleab Alemayehu Kinfu, Pratik Chaudhari, Ben Baker, Anna Schapiro, Dinesh Jayaraman, Eric Eaton, Michael Platt, Lyle Ungar, Leila Wehbe, Ádám Kepecs, Amy Christensen, Onyema Osuagwu, Bing Brunton, Brett Mensh, Alysson R. Muotri, Gabriel A. Silva, Francesca Puppo, Florian Engert, Elizabeth Hillman, Julia Brown, Chris White, Weiwei Yang
Prospective Learning: Back to the Future. CoRR (2022)
Rahul Ramesh, Jialin Mao, Itay Griniasty, Rubing Yang, Han Kheng Teoh, Mark K. Transtrum, James P. Sethna, Pratik Chaudhari
A picture of the space of typical learnable tasks. CoRR (2022)
Yansong Gao, Rahul Ramesh, Pratik Chaudhari
Deep Reference Priors: What is the best way to pretrain a model? CoRR (2022)
Rasool Fakoor, Jonas Mueller, Pratik Chaudhari, Alexander J. Smola
Continuous Doubly Constrained Batch Reinforcement Learning. CoRR (2021)
Rasool Fakoor, Jonas Mueller, Kavosh Asadi, Pratik Chaudhari, Alexander J. Smola
Continuous Doubly Constrained Batch Reinforcement Learning. NeurIPS (2021)
Yansong Gao, Pratik Chaudhari
A free-energy principle for representation learning. Mach. Learn. Sci. Technol. 2 (4) (2021)
Rahul Ramesh, Pratik Chaudhari
Boosting a Model Zoo for Multi-Task and Continual Learning. CoRR (2021)
Rubing Yang, Jialin Mao, Pratik Chaudhari
Does the Data Induce Capacity Control in Deep Learning? CoRR (2021)
Ty Nguyen, Ian D. Miller, Avi Cohen, Dinesh Thakur, Arjun Guru, Shashank Prasad, Camillo J. Taylor, Pratik Chaudhari, Vijay Kumar
PennSyn2Real: Training Object Recognition Models Without Human Labeling. IEEE Robotics Autom. Lett. 6 (3) (2021)
Rongguang Wang, Pratik Chaudhari, Christos Davatzikos
Embracing the Disharmony in Heterogeneous Medical Data. CoRR (2021)
Yansong Gao, Pratik Chaudhari
An Information-Geometric Distance on the Space of Tasks. ICML (2021)
Rongguang Wang, Pratik Chaudhari, Christos Davatzikos
Harmonization with Flow-based Causal Inference. CoRR (2021)
Wenbo Zhang, Karl Schmeckpeper, Pratik Chaudhari, Kostas Daniilidis
Deformable Linear Object Prediction Using Locally Linear Latent Dynamics. ICRA (2021)
Wenbo Zhang, Karl Schmeckpeper, Pratik Chaudhari, Kostas Daniilidis
Deformable Linear Object Prediction Using Locally Linear Latent Dynamics. CoRR (2021)
Xiaoyi Chen, Pratik Chaudhari
MIDAS: Multi-agent Interaction-aware Decision-making with Adaptive Strategies for Urban Autonomous Navigation. ICRA (2021)
Christopher D. Hsu, Heejin Jeong, George J. Pappas, Pratik Chaudhari
Scalable Reinforcement Learning Policies for Multi-Agent Control. IROS (2021)
Rongguang Wang, Pratik Chaudhari, Christos Davatzikos
Harmonization with Flow-Based Causal Inference. MICCAI (3) (2021)
Yansong Gao, Pratik Chaudhari
A Free-Energy Principle for Representation Learning. ICML (2020)
Rasool Fakoor, Jonas Mueller, Nick Erickson, Pratik Chaudhari, Alexander J. Smola
Fast, Accurate, and Simple Models for Tabular Data via Augmented Distillation. NeurIPS (2020)
Rasool Fakoor, Pratik Chaudhari, Jonas Mueller, Alexander J. Smola
TraDE: Transformers for Density Estimation. CoRR (2020)
Hao Li, Pratik Chaudhari, Hao Yang, Michael Lam, Avinash Ravichandran, Rahul Bhotika, Stefano Soatto
Rethinking the Hyperparameters for Fine-tuning. CoRR (2020)
Achin Jain, Pratik Chaudhari, Manfred Morari
BayesRace: Learning to race autonomously using prior experience. CoRR (2020)
Christopher D. Hsu, Heejin Jeong, George J. Pappas, Pratik Chaudhari
Scalable Reinforcement Learning Policies for Multi-Agent Control. CoRR (2020)
Rasool Fakoor, Pratik Chaudhari, Stefano Soatto, Alexander J. Smola
Meta-Q-Learning. ICLR (2020)
Yansong Gao, Pratik Chaudhari
An Information-Geometric Distance on the Space of Tasks. CoRR (2020)
Marco Maggipinto, Gian Antonio Susto, Pratik Chaudhari
Proximal Deterministic Policy Gradient. CoRR (2020)
Achin Jain, Matthew O'Kelly, Pratik Chaudhari, Manfred Morari
BayesRace: Learning to race autonomously using prior experience. CoRL (2020)
Matteo Terzi, Gian Antonio Susto, Pratik Chaudhari
Directional adversarial training for cost sensitive deep learning classification applications. Eng. Appl. Artif. Intell. 91 (2020)
Guneet Singh Dhillon, Pratik Chaudhari, Avinash Ravichandran, Stefano Soatto
A Baseline for Few-Shot Image Classification. ICLR (2020)
Rita Fioresi, Pratik Chaudhari, Stefano Soatto
A Geometric Interpretation of Stochastic Gradient Descent Using Diffusion Metrics. Entropy 22 (1) (2020)
Rasool Fakoor, Pratik Chaudhari, Alexander J. Smola
DDPG++: Striving for Simplicity in Continuous-control Off-Policy Reinforcement Learning. CoRR (2020)
Marco Maggipinto, Gian Antonio Susto, Pratik Chaudhari
Proximal Deterministic Policy Gradient. IROS (2020)
Andrew Hua, Pratik Chaudhari, Nicole Johnson, Joshua Quinton, Bruce R. Schatz, David Buchner, Manuel E. Hernandez
Evaluation of Machine Learning Models for Classifying Upper Extremity Exercises Using Inertial Measurement Unit-Based Kinematic Data. IEEE J. Biomed. Health Informatics 24 (9) (2020)
Xiaoyi Chen, Pratik Chaudhari
MIDAS: Multi-agent Interaction-aware Decision-making with Adaptive Strategies for Urban Autonomous Navigation. CoRR (2020)
Hao Li, Pratik Chaudhari, Hao Yang, Michael Lam, Avinash Ravichandran, Rahul Bhotika, Stefano Soatto
Rethinking the Hyperparameters for Fine-tuning. ICLR (2020)
Rasool Fakoor, Jonas Mueller, Nick Erickson, Pratik Chaudhari, Alexander J. Smola
Fast, Accurate, and Simple Models for Tabular Data via Augmented Distillation. CoRR (2020)
Yansong Gao, Pratik Chaudhari
A Free-Energy Principle for Representation Learning. CoRR (2020)
Matteo Terzi, Gian Antonio Susto, Pratik Chaudhari
Directional Adversarial Training for Cost Sensitive Deep Learning Classification Applications. CoRR (2019)
Rasool Fakoor, Pratik Chaudhari, Alexander J. Smola
P3O: Policy-on Policy-off Policy Optimization. UAI (2019)
Rita Fioresi, Pratik Chaudhari, Stefano Soatto
A geometric interpretation of stochastic gradient descent using diffusion metrics. CoRR (2019)
Rasool Fakoor, Pratik Chaudhari, Alexander J. Smola
P3O: Policy-on Policy-off Policy Optimization. CoRR (2019)
Guneet S. Dhillon, Pratik Chaudhari, Avinash Ravichandran, Stefano Soatto
A Baseline for Few-Shot Image Classification. CoRR (2019)
Rasool Fakoor, Pratik Chaudhari, Stefano Soatto, Alexander J. Smola
Meta-Q-Learning. CoRR (2019)
Pratik Chaudhari, Stefano Soatto
Stochastic Gradient Descent Performs Variational Inference, Converges to Limit Cycles for Deep Networks. ITA (2018)
Pratik Chaudhari, Stefano Soatto
Stochastic gradient descent performs variational inference, converges to limit cycles for deep networks. ICLR (Poster) (2018)
Pratik Chaudhari, Stefano Soatto
Stochastic gradient descent performs variational inference, converges to limit cycles for deep networks. CoRR (2017)
Pratik Chaudhari, Adam M. Oberman, Stanley J. Osher, Stefano Soatto, Guillaume Carlier
Partial differential equations for training deep neural networks. ACSSC (2017)
Pratik Chaudhari, Carlo Baldassi, Riccardo Zecchina, Stefano Soatto, Ameet Talwalkar
Parle: parallelizing stochastic gradient descent. CoRR (2017)
Pratik Chaudhari, Anna Choromanska, Stefano Soatto, Yann LeCun, Carlo Baldassi, Christian Borgs, Jennifer T. Chayes, Levent Sagun, Riccardo Zecchina
Entropy-SGD: Biasing Gradient Descent Into Wide Valleys. ICLR (Poster) (2017)
Pratik Chaudhari, Adam M. Oberman, Stanley J. Osher, Stefano Soatto, Guillaume Carlier
Deep Relaxation: partial differential equations for optimizing deep neural networks. CoRR (2017)
Pratik Chaudhari, Anna Choromanska, Stefano Soatto, Yann LeCun, Carlo Baldassi, Christian Borgs, Jennifer T. Chayes, Levent Sagun, Riccardo Zecchina
Entropy-SGD: Biasing Gradient Descent Into Wide Valleys. CoRR (2016)
Pratik Chaudhari, Stefano Soatto
Trivializing The Energy Landscape Of Deep Networks. CoRR (2015)
Minghui Zhu, Michael W. Otte, Pratik Chaudhari, Emilio Frazzoli
Game theoretic controller synthesis for multi-robot motion planning Part I: Trajectory based algorithms. ICRA (2014)
Pratik Chaudhari, Tichakorn Wongpiromsarn, Emilio Frazzoli
Incremental minimum-violation control synthesis for robots interacting with external agents. ACC (2014)
Valerio Varricchio, Pratik Chaudhari, Emilio Frazzoli
Sampling-based algorithms for optimal motion planning using process algebra specifications. ICRA (2014)
Minghui Zhu, Michael W. Otte, Pratik Chaudhari, Emilio Frazzoli
Game theoretic controller synthesis for multi-robot motion planning Part I : Trajectory based algorithms. CoRR (2014)

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Publication Activity (10 Years)

Top Topics

Top Venues

Pratik Chaudhari