P. Chaudhari

发表

The Effect of Gradient Noise on the Energy Landscape of Deep Networks

P. Chaudhari, Stefano Soatto, 2015 .

On the energy landscape of deep networks

Stefano Soatto, Pratik Chaudhari, P. Chaudhari, 2015, 1511.06485.

Entropy-SGD: biasing gradient descent into wide valleys pdf

Stefano Soatto, Yann LeCun, Christian Borgs, 2016, ICLR.

Stochastic Gradient Descent Performs Variational Inference, Converges to Limit Cycles for Deep Networks

Stefano Soatto, Pratik Chaudhari, P. Chaudhari, 2017, 2018 Information Theory and Applications Workshop (ITA).

Partial differential equations for training deep neural networks

Stefano Soatto, Stanley Osher, Adam M. Oberman, 2017, 2017 51st Asilomar Conference on Signals, Systems, and Computers.

Deep relaxation: partial differential equations for optimizing deep neural networks

Stefano Soatto, Stanley Osher, Adam M. Oberman, 2017, Research in the Mathematical Sciences.

TraDE: Transformers for Density Estimation pdf

Alexander J. Smola, Rasool Fakoor, Pratik Chaudhari, 2020, ArXiv.

Appendix: A Baseline for Few-Shot Image Classification

Guneet Singh Dhillon, P. Chaudhari, Stefano Soatto, 2019 .

Incremental minimum-violation control synthesis for robots interacting with external agents

Emilio Frazzoli, Pratik Chaudhari, Tichakorn Wongpiromsarn, 2014, 2014 American Control Conference.

MIDAS: Multi-agent Interaction-aware Decision-making with Adaptive Strategies for Urban Autonomous Navigation

P. Chaudhari, Xiaoyi Chen, 2020, 2021 IEEE International Conference on Robotics and Automation (ICRA).

Disturbance observer based sliding mode control for anti-lock braking system

Vivek Sharma, Pratik Chaudhari, P.D. Shendge, 2016, 2016 IEEE 1st International Conference on Power Electronics, Intelligent Control and Energy Systems (ICPEICES).

Deep Reference Priors: What is the best way to pretrain a model?

P. Chaudhari, Yansong Gao, Rahul Ramesh, 2022, ICML.

S PARSE N EURAL A DDITIVE M ODEL : I NTERPRETABLE D EEP L EARNING WITH F EATURE S ELECTION VIA G S

P. Chaudhari, Zhiqi Bu, Shibiao Xu, 2022 .

Does the Data Induce Capacity Control in Deep Learning?

P. Chaudhari, Rubing Yang, J. Mao, 2021, ICML.

A Model for Perimeter-Defense Problems with Heterogeneous Teams

P. Chaudhari, M. Haile, Christopher Hsu, 2022, ArXiv.

Sparse Neural Additive Model: Interpretable Deep Learning with Feature Selection via Group Sparsity

P. Chaudhari, I. Barnett, Zhiqi Bu, 2022, ECML/PKDD.

Data drift correction via time-varying importance weight estimator

Zachary Chase Lipton, Alexander J. Smola, P. Chaudhari, 2022, ArXiv.

The Value of Out-of-Distribution Data

Ashwin De Silva, Carey E. Priebe, P. Chaudhari, 2022, ArXiv.

A picture of the space of typical learnable tasks

P. Chaudhari, J. Sethna, M. Transtrum, 2022, ArXiv.

How Occam’s razor guides human decision-making

J. Gold, P. Chaudhari, V. Balasubramanian, 2023, bioRxiv.

Rethinking the Hyperparameters for Fine-tuning pdf

Stefano Soatto, Avinash Ravichandran, Rahul Bhotika, 2020, ICLR.

Deep relaxation: partial differential equations for optimizing deep neural networks

Adam M. Oberman, P. Chaudhari, S. Osher, 2018, Research in the Mathematical Sciences.

A Baseline for Few-Shot Image Classification pdf

Stefano Soatto, Avinash Ravichandran, Guneet S. Dhillon, 2019, ICLR.

Time as a supervisor: temporal regularity and auditory object learning

P. Chaudhari, Y. Cohen, V. Balasubramanian, 2022, bioRxiv.

Harmonization with Flow-based Causal Inference

P. Chaudhari, C. Davatzikos, Rongguang Wang, 2021, MICCAI.

Embracing the disharmony in medical imaging: A Simple and effective framework for domain adaptation

Christos Davatzikos, Pratik Chaudhari, Rongguang Wang, 2021, Medical Image Anal..

Continuous Doubly Constrained Batch Reinforcement Learning pdf

Alexander J. Smola, Rasool Fakoor, Jonas Mueller, 2021, NeurIPS.

Beyond mAP: Towards Better Evaluation of Instance Segmentation

Vivek P. Buch, P. Chaudhari, Rohit Jena, 2022, 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

Model Zoo: A Growing Brain That Learns Continually

P. Chaudhari, Rahul Ramesh, 2021, ICLR.

Learning under Data Drift with Time-Varying Importance Weights

Zachary Chase Lipton, Alexander J. Smola, P. Chaudhari, 2022, 2210.01422.

An Information-Geometric Distance on the Space of Tasks pdf

Yansong Gao, Pratik Chaudhari, P. Chaudhari, 2020, ICML.

P3O: Policy-on Policy-off Policy Optimization pdf

Alexander J. Smola, Rasool Fakoor, Pratik Chaudhari, 2019, UAI.

The Value of Out-of-Distribution Data

Ashwin De Silva, Carey E. Priebe, P. Chaudhari, 2022, arXiv.org.

Meta-Q-Learning

Alex Smola, P. Chaudhari, Stefano Soatto, 2019, ICLR.

Fast, Accurate, and Simple Models for Tabular Data via Augmented Distillation pdf

Alexander J. Smola, Rasool Fakoor, Pratik Chaudhari, 2020, NeurIPS.

Incremental sampling-based algorithm for minimum-violation motion planning

Emilio Frazzoli, Daniela Rus, Sertac Karaman, 2013, 52nd IEEE Conference on Decision and Control.

Algorithms for minimum-violation planning with formal specifications

Sertac Karaman, Pratik Chaudhari, Jana Tůmová, 2014 .

Time as a supervisor: temporal regularity and auditory object learning

P. Chaudhari, Y. Cohen, V. Balasubramanian, 2023, bioRxiv.

Game theoretic controller synthesis for multi-robot motion planning Part I: Trajectory based algorithms

Emilio Frazzoli, Minghui Zhu, Pratik Chaudhari, 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).

Algorithms for autonomous urban navigation with formal specifications

Pratik Chaudhari, P. Chaudhari, 2014 .

A picture of the space of typical learnable tasks

P. Chaudhari, J. Sethna, M. Transtrum, 2022, ArXiv.

Learning Capacity: A Measure of the Effective Dimensionality of a Model

P. Chaudhari, Wei-Di Chang, Daiwei Chen, 2023, ArXiv.

A Free-Energy Principle for Representation Learning pdf

Yansong Gao, Pratik Chaudhari, P. Chaudhari, 2020, ICML.

The Training Process of Many Deep Networks Explores the Same Low-Dimensional Manifold

P. Chaudhari, J. Sethna, M. Transtrum, 2023, arXiv.org.

Taming AI Bots: Controllability of Neural States in Large Language Models

P. Chaudhari, P. Tabuada, S. Soatto, 2023, ArXiv.

Directional Adversarial Training for Cost Sensitive Deep Learning Classification Applications pdf

Pratik Chaudhari, Matteo Terzi, Gian Antonio Susto, 2019, Eng. Appl. Artif. Intell..

Learning under Data Drift with Time-Varying Importance Weights

Zachary Chase Lipton, Alexander J. Smola, P. Chaudhari, 2022, 2210.01422.

DDPG++: Striving for Simplicity in Continuous-control Off-Policy Reinforcement Learning pdf

Alexander J. Smola, Rasool Fakoor, Pratik Chaudhari, 2020, ArXiv.

Boosting a Model Zoo for Multi-Task and Continual Learning pdf

Pratik Chaudhari, Rahul Ramesh, P. Chaudhari, 2021, ArXiv.

How Occam’s razor guides human decision-making

J. Gold, P. Chaudhari, V. Balasubramanian, 2023, bioRxiv.

Scalable Reinforcement Learning Policies for Multi-Agent Control

George J. Pappas, Pratik Chaudhari, Heejin Jeong, 2020, 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

A Picture of the Energy Landscape of Deep Neural Networks

Pratik Anil Chaudhari, P. Chaudhari, 2018 .

The Training Process of Many Deep Networks Explores the Same Low-Dimensional Manifold

P. Chaudhari, J. Sethna, M. Transtrum, 2023, ArXiv.

Deformable Linear Object Prediction Using Locally Linear Latent Dynamics

Kostas Daniilidis, Pratik Chaudhari, Karl Schmeckpeper, 2021, 2021 IEEE International Conference on Robotics and Automation (ICRA).

Mesh Strikes Back: Fast and Efficient Human Reconstruction from RGB videos

Brandon M. Smith, P. Chaudhari, Siddharth Choudhary, 2023, ArXiv.

Fast Diffusion Probabilistic Model Sampling through the lens of Backward Error Analysis

P. Chaudhari, Xiaoxia Zhou, Yansong Gao, 2023, ArXiv.

Parle: parallelizing stochastic gradient descent pdf

Ameet Talwalkar, Stefano Soatto, Carlo Baldassi, 2017, ArXiv.

A picture of the space of typical learnable tasks

P. Chaudhari, J. Sethna, M. Transtrum, 2022, ICML.

Proximal Deterministic Policy Gradient pdf

Pratik Chaudhari, Marco Maggipinto, Gian Antonio Susto, 2020, 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

BayesRace: Learning to race autonomously using prior experience pdf

Manfred Morari, Pratik Chaudhari, Achin Jain, 2020, CoRL.

Prospective Learning: Principled Extrapolation to the Future

Elizabeth L. Ogburn, Adam S. Charles, Justus M. Kebschull, 2022, 2201.07372.

Learning the Learning Rate for Gradient Descent by Gradient Descent

P. Chaudhari, Michele Donini, Orchid Majumder, 2019 .

The Value of Out-of-Distribution Data

Ashwin De Silva, Carey E. Priebe, P. Chaudhari, 2022, ICML.

Incremental sampling based algorithms for state estimation

Pratik Chaudhari, P. Chaudhari, 2012 .

Zecchina Learning by Local Entropy Maximization : the effective landscape of neural networks learning algorithms

P. Chaudhari, Stefano Soatto, 2017 .

Time-Varying Propensity Score to Bridge the Gap between the Past and Present

Zachary Chase Lipton, Alexander J. Smola, P. Chaudhari, 2022, 2210.01422.

A Baseline for Few-Shot Image Classification

Guneet Singh Dhillon, P. Chaudhari, Stefano Soatto, 2019, ICLR.