Localization using Average Landmark Vector in the Presence of Clutter. - Pratik Chaudhari (NaBIC, 2009)

Sampling-based algorithm for filtering using Markov chain approximations. - Pratik Chaudhari; Sertac Karaman; Emilio Frazzoli (CDC, 2012)

Sampling-based algorithms for continuous-time POMDPs. - Pratik Chaudhari; Sertac Karaman; David Hsu; Emilio Frazzoli (ACC, 2013)

Incremental sampling-based algorithm for minimum-violation motion planning. - Luis I. Reyes Castro; Pratik Chaudhari; Jana Tumova; Sertac Karaman; Emilio Frazzoli; Daniela Rus (CDC, 2013)

Incremental minimum-violation control synthesis for robots interacting with external agents. - Pratik Chaudhari; Tichakorn Wongpiromsarn; Emilio Frazzoli (ACC, 2014)

Sampling-based algorithms for optimal motion planning using process algebra specifications. - Valerio Varricchio; Pratik Chaudhari; Emilio Frazzoli (ICRA, 2014)

Game theoretic controller synthesis for multi-robot motion planning Part I: Trajectory based algorithms. - Minghui Zhu; Michael W. Otte; Pratik Chaudhari; Emilio Frazzoli (ICRA, 2014)

Trivializing The Energy Landscape Of Deep Networks. - Pratik Chaudhari; Stefano Soatto (CoRR, 2015)

Partial differential equations for training deep neural networks. - Pratik Chaudhari; Adam M. Oberman; Stanley J. Osher; Stefano Soatto; Guillaume Carlier (ACSSC, 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 (ICLR (Poster), 2017)

Parle: parallelizing stochastic gradient descent. - Pratik Chaudhari; Carlo Baldassi; Riccardo Zecchina; Stefano Soatto; Ameet Talwalkar (CoRR, 2017)

Deep Relaxation: partial differential equations for optimizing deep neural networks. - Pratik Chaudhari; Adam M. Oberman; Stanley J. Osher; Stefano Soatto; Guillaume Carlier (CoRR, 2017)

Stochastic gradient descent performs variational inference, converges to limit cycles for deep networks. - Pratik Chaudhari; Stefano Soatto (ICLR (Poster), 2018)

P3O: Policy-on Policy-off Policy Optimization. - Rasool Fakoor; Pratik Chaudhari; Alexander J. Smola (UAI, 2019)

BayesRace: Learning to race autonomously using prior experience. - Achin Jain; Matthew O'Kelly; Pratik Chaudhari; Manfred Morari (CoRL, 2020)

A Baseline for Few-Shot Image Classification. - Guneet Singh Dhillon; Pratik Chaudhari; Avinash Ravichandran; Stefano Soatto (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 043; Michael Lam; Avinash Ravichandran; Rahul Bhotika; Stefano Soatto (ICLR, 2020)

Proximal Deterministic Policy Gradient. - Marco Maggipinto; Gian Antonio Susto; Pratik Chaudhari (IROS, 2020)

Fast, Accurate, and Simple Models for Tabular Data via Augmented Distillation. - Rasool Fakoor; Jonas Mueller 001; Nick Erickson; Pratik Chaudhari; Alexander J. Smola (NeurIPS, 2020)

TraDE: Transformers for Density Estimation. - Rasool Fakoor; Pratik Chaudhari; Jonas Mueller 001; Alexander J. Smola (CoRR, 2020)

BayesRace: Learning to race autonomously using prior experience. - Achin Jain; Pratik Chaudhari; Manfred Morari (CoRR, 2020)

DDPG++: Striving for Simplicity in Continuous-control Off-Policy Reinforcement Learning. - Rasool Fakoor; Pratik Chaudhari; Alexander J. Smola (CoRR, 2020)

Directional adversarial training for cost sensitive deep learning classification applications. - Matteo Terzi; Gian Antonio Susto; Pratik Chaudhari (Eng. Appl. Artif. Intell., 2020)

A Geometric Interpretation of Stochastic Gradient Descent Using Diffusion Metrics. - Rita Fioresi; Pratik Chaudhari; Stefano Soatto (Entropy, 2020)

Evaluation of Machine Learning Models for Classifying Upper Extremity Exercises Using Inertial Measurement Unit-Based Kinematic Data. - Andrew Hua; Pratik Chaudhari; Nicole Johnson; Joshua Quinton; Bruce R. Schatz; David Buchner; Manuel E. Hernandez (IEEE J. Biomed. Health Informatics, 2020)

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

MIDAS: Multi-agent Interaction-aware Decision-making with Adaptive Strategies for Urban Autonomous Navigation. - Xiaoyi Chen; Pratik Chaudhari (ICRA, 2021)

Deformable Linear Object Prediction Using Locally Linear Latent Dynamics. - Wenbo Zhang; Karl Schmeckpeper; Pratik Chaudhari; Kostas Daniilidis (ICRA, 2021)

Scalable Reinforcement Learning Policies for Multi-Agent Control. - Christopher D. Hsu; Heejin Jeong; George J. Pappas; Pratik Chaudhari (IROS, 2021)

Harmonization with Flow-Based Causal Inference. - Rongguang Wang; Pratik Chaudhari; Christos Davatzikos (MICCAI (3), 2021)

Continuous Doubly Constrained Batch Reinforcement Learning. - Rasool Fakoor; Jonas Mueller 001; Kavosh Asadi; Pratik Chaudhari; Alexander J. Smola (NeurIPS, 2021)

Continuous Doubly Constrained Batch Reinforcement Learning. - Rasool Fakoor; Jonas Mueller 001; Pratik Chaudhari; Alexander J. Smola (CoRR, 2021)

Embracing the Disharmony in Heterogeneous Medical Data. - Rongguang Wang; Pratik Chaudhari; Christos Davatzikos (CoRR, 2021)

Boosting a Model Zoo for Multi-Task and Continual Learning. - Rahul Ramesh; Pratik Chaudhari (CoRR, 2021)

A free-energy principle for representation learning. - Yansong Gao; Pratik Chaudhari (Mach. Learn. Sci. Technol., 2021)

PennSyn2Real: Training Object Recognition Models Without Human Labeling. - Ty Nguyen; Ian D. Miller; Avi Cohen; Dinesh Thakur; Arjun Guru; Shashank Prasad; Camillo J. Taylor; Pratik Chaudhari; Vijay Kumar 001 (IEEE Robotics Autom. Lett., 2021)

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

Model Zoo: A Growing Brain That Learns Continually. - Rahul Ramesh; Pratik Chaudhari (ICLR, 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 (ICML, 2022)

Prospective Learning: Back to the Future. - Joshua T. Vogelstein; Timothy D. 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; et al. (CoRR, 2022)

Machine Learning Models Are Not Necessarily Biased When Constructed Properly: Evidence from Neuroimaging Studies. - Rongguang Wang; Pratik Chaudhari; Christos Davatzikos (CoRR, 2022)

MammoDL: Mammographic Breast Density Estimation using Federated Learning. - Keshava Katti; Ramya Muthukrishnan; Angelina Heyler; Sarthak Pati; Aprupa Alahari; Michael Sanborn; Emily F. Conant; Christopher G. Scott; Stacey J. Winham; Celine M. Vachon; Pratik Chaudhari; Despina Kontos; et al. (CoRR, 2022)

A Model for Perimeter-Defense Problems with Heterogeneous Teams. - Christopher D. Hsu; Mulugeta A. Haile; Pratik Chaudhari (CoRR, 2022)

Data drift correction via time-varying importance weight estimator. - Rasool Fakoor; Jonas Mueller 001; Zachary C. Lipton; Pratik Chaudhari; Alexander J. Smola (CoRR, 2022)

Embracing the disharmony in medical imaging: A Simple and effective framework for domain adaptation. - Rongguang Wang; Pratik Chaudhari; Christos Davatzikos (Medical Image Anal., 2022)

Prospective Learning: Principled Extrapolation to the Future. - Ashwin De Silva; Rahul Ramesh; Lyle H. Ungar; Marshall G. Hussain Shuler; Noah J. Cowan; Michael L. Platt; Chen Li; Leyla Isik; Seung-Eon Roh; Adam S. Charles; Archana Venkataraman; Brian Caffo; et al. (CoLLAs, 2023)

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

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

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

Budgeting Counterfactual for Offline RL. - Yao Liu 009; Pratik Chaudhari; Rasool Fakoor (NeurIPS, 2023)

Sparse Neural Additive Model: Interpretable Deep Learning with Feature Selection via Group Sparsity. - Shiyun Xu; Zhiqi Bu; Pratik Chaudhari; Ian J. Barnett (ECML/PKDD (3), 2023)

Mesh Strikes Back: Fast and Efficient Human Reconstruction from RGB videos. - Rohit Jena; Pratik Chaudhari; James C. Gee; Ganesh Subramanian Iyer; Siddharth Choudhary; Brandon M. Smith 001 (CoRR, 2023)

Fast Diffusion Probabilistic Model Sampling through the lens of Backward Error Analysis. - Yansong Gao; Zhihong Pan 001; Xin Zhou 017; Le Kang; Pratik Chaudhari (CoRR, 2023)

The Training Process of Many Deep Networks Explores the Same Low-Dimensional Manifold. - Jialin Mao; Itay Griniasty; Han Kheng Teoh; Rahul Ramesh; Rubing Yang; Mark K. Transtrum; James P. Sethna; Pratik Chaudhari (CoRR, 2023)

Learning Capacity: A Measure of the Effective Dimensionality of a Model. - Daiwei Chen; Weikai Chang; Pratik Chaudhari (CoRR, 2023)

Taming AI Bots: Controllability of Neural States in Large Language Models. - Stefano Soatto; Paulo Tabuada; Pratik Chaudhari; Tian Yu Liu (CoRR, 2023)

Adapting Machine Learning Diagnostic Models to New Populations Using a Small Amount of Data: Results from Clinical Neuroscience. - Rongguang Wang; Güray Erus; Pratik Chaudhari; Christos Davatzikos (CoRR, 2023)

Analog Content-Addressable Memory from Complementary FeFETs. - Xiwen Liu; Keshava Katti; Yunfei He; Paul Jacob; Claudia Richter; Uwe Schroeder; Santosh Kurinec; Pratik Chaudhari; Deep Jariwala (CoRR, 2023)

Design and Evaluation of Motion Planners for Quadrotors. - Yifei Simon Shao; Yuwei Wu 005; Laura Jarin-Lipschitz; Pratik Chaudhari; Vijay Kumar 001 (CoRR, 2023)

SplatArmor: Articulated Gaussian splatting for animatable humans from monocular RGB videos. - Rohit Jena; Ganesh Subramanian Iyer; Siddharth Choudhary; Brandon M. Smith 001; Pratik Chaudhari; James C. Gee (CoRR, 2023)

Retrieving Conditions from Reference Images for Diffusion Models. - Haoran Tang; Xin Zhou 017; Jieren Deng; Zhihong Pan 001; Hao Tian 005; Pratik Chaudhari (CoRR, 2023)

Time as a supervisor: temporal regularity and auditory object learning. - Ronald W. Ditullio; Chetan Parthiban; Eugenio Piasini; Pratik Chaudhari; Vijay Balasubramanian; Yale E. Cohen (Frontiers Comput. Neurosci., 2023)

Active Perception using Neural Radiance Fields. - Siming He; Christopher D. Hsu; Dexter Ong; Yifei Simon Shao; Pratik Chaudhari (ACC, 2024)

A Model for Multi-Agent Heterogeneous Interaction Problems. - Christopher D. Hsu; Mulugeta A. Haile; Pratik Chaudhari (ACC, 2024)

Heat Death of Generative Models in Closed-Loop Learning. - Matteo Marchi; Stefano Soatto; Pratik Chaudhari; Paulo Tabuada (CDC, 2024)

Time-Varying Propensity Score to Bridge the Gap between the Past and Present. - Rasool Fakoor; Jonas Mueller 001; Zachary Chase Lipton; Pratik Chaudhari; Alex Smola (ICLR, 2024)

TreeScope: An Agricultural Robotics Dataset for LiDAR-Based Mapping of Trees in Forests and Orchards. - Derek Cheng; Fernando Cladera Ojeda; Ankit Prabhu; Xu Liu 007; Alan Zhu 002; Patrick Corey Green; Reza Ehsani; Pratik Chaudhari; Vijay Kumar 001 (ICRA, 2024)

Design and Evaluation of Motion Planners for Quadrotors in Environments with Varying Complexities. - Yifei Simon Shao; Yuwei Wu 005; Laura Jarin-Lipschitz; Pratik Chaudhari; Vijay Kumar 001 (ICRA, 2024)

Active Scout: Multi-Target Tracking Using Neural Radiance Fields in Dense Urban Environments. - Christopher D. Hsu; Pratik Chaudhari (IROS, 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 (NeurIPS, 2024)

Constraint-Aware Intent Estimation for Dynamic Human-Robot Object Co-Manipulation. - Yifei Simon Shao; Tianyu Li; Shafagh Keyvanian; Pratik Chaudhari; Vijay Kumar 001; Nadia Figueroa (Robotics: Science and Systems, 2024)

An Active Perception Game for Robust Autonomous Exploration. - Siming He; Yuezhan Tao; Igor Spasojevic; Vijay Kumar 001; Pratik Chaudhari (CoRR, 2024)

FireANTs: Adaptive Riemannian Optimization for Multi-Scale Diffeomorphic Registration. - Rohit Jena; Pratik Chaudhari; James C. Gee (CoRR, 2024)

From NeRFs to Gaussian Splats, and Back. - Siming He; Zach Osman; Pratik Chaudhari (CoRR, 2024)

Meanings and Feelings of Large Language Models: Observability of Latent States in Generative AI. - Tian Yu Liu; Stefano Soatto; Matteo Marchi; Pratik Chaudhari; Paulo Tabuada (CoRR, 2024)

Deep Implicit Optimization for Robust and Flexible Image Registration. - Rohit Jena; Pratik Chaudhari; James C. Gee (CoRR, 2024)

Optimal Convex Cover as Collision-free Space Approximation for Trajectory Generation. - Yuwei Wu 005; Igor Spasojevic; Pratik Chaudhari; Vijay Kumar 001 (CoRR, 2024)

SlideSLAM: Sparse, Lightweight, Decentralized Metric-Semantic SLAM for Multi-Robot Navigation. - Xu Liu 007; Jiuzhou Lei; Ankit Prabhu; Yuezhan Tao; Igor Spasojevic; Pratik Chaudhari; Nikolay Atanasov 001; Vijay Kumar 001 (CoRR, 2024)

Many Perception Tasks are Highly Redundant Functions of their Input Data. - Rahul Ramesh; Anthony Bisulco; Ronald W. Ditullio; Linran Wei; Vijay Balasubramanian; Kostas Daniilidis; Pratik Chaudhari (CoRR, 2024)

A Confidence Interval for the ℓ2 Expected Calibration Error. - Yan Sun; Pratik Chaudhari; Ian J. Barnett; Edgar Dobriban (CoRR, 2024)

RT-GuIDE: Real-Time Gaussian splatting for Information-Driven Exploration. - Yuezhan Tao; Dexter Ong; Varun Murali; Igor Spasojevic; Pratik Chaudhari; Vijay Kumar 001 (CoRR, 2024)

4D Metric-Semantic Mapping for Persistent Orchard Monitoring: Method and Dataset. - Jiuzhou Lei; Ankit Prabhu; Xu Liu 007; Fernando Cladera Ojeda; Mehrad Mortazavi; Reza Ehsani; Pratik Chaudhari; Vijay Kumar 001 (CoRR, 2024)

dSTAR: Straggler Tolerant and Byzantine Resilient Distributed SGD. - Jiahe Yan; Pratik Chaudhari; Leonard Kleinrock (CoRR, 2024)

Don't Yell at Your Robot: Physical Correction as the Collaborative Interface for Language Model Powered Robots. - Chuye Zhang; Yifei Simon Shao; Harshil Parekh; Junyao Shi; Pratik Chaudhari; Vijay Kumar 001; Nadia Figueroa (CoRR, 2024)

Prospective Learning in Retrospect. - Yuxin Bai; Cecelia Shuai; Ashwin De Silva; Siyu Yu; Pratik Chaudhari; Joshua T. Vogelstein (AGI (1), 2025)

AgentOccam: A Simple Yet Strong Baseline for LLM-Based Web Agents. - Ke Yang 003; Yao Liu 009; Sapana Chaudhary; Rasool Fakoor; Pratik Chaudhari; George Karypis; Huzefa Rangwala (ICLR, 2025)

Observability of Latent States in Generative AI Models. - Tian Yu Liu; Stefano Soatto; Matteo Marchi; Pratik Chaudhari; Paulo Tabuada (NeuS, 2025)

Deep implicit optimization enables robust learnable features for deformable image registration. - Rohit Jena; Pratik Chaudhari; James C. Gee (Medical Image Anal., 2025)

Bridging the Training-Inference Gap in LLMs by Leveraging Self-Generated Tokens. - Zhepeng Cen; Yao Liu 009; Siliang Zeng; Pratik Chaudhari; Huzefa Rangwala; George Karypis; Rasool Fakoor (Trans. Mach. Learn. Res., 2025)

ATLAS Navigator: Active Task-driven LAnguage-embedded Gaussian Splatting. - Dexter Ong; Yuezhan Tao; Varun Murali; Igor Spasojevic; Vijay Kumar 001; Pratik Chaudhari (CoRR, 2025)

An Effective Gram Matrix Characterizes Generalization in Deep Networks. - Rubing Yang; Pratik Chaudhari (CoRR, 2025)

Estimating the Diameter at Breast Height of Trees in a Forest With a Single 360 Camera. - Siming He; Zachary Osman; Fernando Cladera; Dexter Ong; Nitant Rai; Patrick Corey Green; Vijay Kumar 001; Pratik Chaudhari (CoRR, 2025)

An Analytical Characterization of Sloppiness in Neural Networks: Insights from Linear Models. - Jialin Mao; Itay Griniasty; Yan Sun; Mark K. Transtrum; James P. Sethna; Pratik Chaudhari (CoRR, 2025)

Gaussian Splatting as a Unified Representation for Autonomy in Unstructured Environments. - Dexter Ong; Yuezhan Tao; Varun Murali; Igor Spasojevic; Vijay Kumar 001; Pratik Chaudhari (CoRR, 2025)

Towards Optimizing a Convex Cover of Collision-Free Space for Trajectory Generation. - Yuwei Wu 005; Igor Spasojevic; Pratik Chaudhari; Vijay Kumar 001 (IEEE Robotics Autom. Lett., 2025)

Learning a Vision-Based Footstep Planner for Hierarchical Walking Control. - Minku Kim; Brian Acosta; Pratik Chaudhari; Michael Posa (CoRR, 2025)

From Linearity to Non-Linearity: How Masked Autoencoders Capture Spatial Correlations. - Anthony Bisulco; Rahul Ramesh; Randall Balestriero; Pratik Chaudhari (CoRR, 2025)

Spatio-Temporal Metric-Semantic Mapping for Persistent Orchard Monitoring: Method and Dataset. - Jiuzhou Lei; Ankit Prabhu; Xu Liu 007; Fernando Cladera; Mehrad Mortazavi; Reza Ehsani; Pratik Chaudhari; Vijay Kumar 001 (IEEE Robotics Autom. Lett., 2025)