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2020 – today
- 2022
[j5]Rongguang Wang, Pratik Chaudhari, Christos Davatzikos:
Embracing the disharmony in medical imaging: A Simple and effective framework for domain adaptation. Medical Image Anal. 76: 102309 (2022)- [i31]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 abs/2201.07372 (2022) - [i30]Yansong Gao, Rahul Ramesh, Pratik Chaudhari:
Deep Reference Priors: What is the best way to pretrain a model? CoRR abs/2202.00187 (2022) - [i29]Shiyun Xu, Zhiqi Bu, Pratik Chaudhari, Ian J. Barnett:
Sparse Neural Additive Model: Interpretable Deep Learning with Feature Selection via Group Sparsity. CoRR abs/2202.12482 (2022) - 2021
- [j4]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): 5032-5039 (2021) - [c25]Yansong Gao, Pratik Chaudhari:
An Information-Geometric Distance on the Space of Tasks. ICML 2021: 3553-3563 - [c24]Xiaoyi Chen, Pratik Chaudhari:
MIDAS: Multi-agent Interaction-aware Decision-making with Adaptive Strategies for Urban Autonomous Navigation. ICRA 2021: 7980-7986 - [c23]Wenbo Zhang, Karl Schmeckpeper, Pratik Chaudhari, Kostas Daniilidis:
Deformable Linear Object Prediction Using Locally Linear Latent Dynamics. ICRA 2021: 13503-13509 - [c22]Christopher D. Hsu, Heejin Jeong, George J. Pappas, Pratik Chaudhari:
Scalable Reinforcement Learning Policies for Multi-Agent Control. IROS 2021: 4785-4791 - [c21]Rongguang Wang, Pratik Chaudhari, Christos Davatzikos:
Harmonization with Flow-Based Causal Inference. MICCAI (3) 2021: 181-190 - [c20]Rasool Fakoor, Jonas Mueller, Kavosh Asadi, Pratik Chaudhari, Alexander J. Smola:
Continuous Doubly Constrained Batch Reinforcement Learning. NeurIPS 2021: 11260-11273 - [i28]Rasool Fakoor, Jonas Mueller, Pratik Chaudhari, Alexander J. Smola:
Continuous Doubly Constrained Batch Reinforcement Learning. CoRR abs/2102.09225 (2021) - [i27]Rongguang Wang, Pratik Chaudhari, Christos Davatzikos:
Embracing the Disharmony in Heterogeneous Medical Data. CoRR abs/2103.12857 (2021) - [i26]Wenbo Zhang, Karl Schmeckpeper, Pratik Chaudhari, Kostas Daniilidis:
Deformable Linear Object Prediction Using Locally Linear Latent Dynamics. CoRR abs/2103.14184 (2021) - [i25]Rahul Ramesh, Pratik Chaudhari:
Boosting a Model Zoo for Multi-Task and Continual Learning. CoRR abs/2106.03027 (2021) - [i24]Rongguang Wang, Pratik Chaudhari, Christos Davatzikos:
Harmonization with Flow-based Causal Inference. CoRR abs/2106.06845 (2021) - [i23]Rubing Yang, Jialin Mao, Pratik Chaudhari:
Does the Data Induce Capacity Control in Deep Learning? CoRR abs/2110.14163 (2021) - 2020
- [j3]Matteo Terzi, Gian Antonio Susto, Pratik Chaudhari:
Directional adversarial training for cost sensitive deep learning classification applications. Eng. Appl. Artif. Intell. 91: 103550 (2020) - [j2]Rita Fioresi, Pratik Chaudhari, Stefano Soatto:
A Geometric Interpretation of Stochastic Gradient Descent Using Diffusion Metrics. Entropy 22(1): 101 (2020) - [j1]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): 2452-2460 (2020) - [c19]Achin Jain, Matthew O'Kelly, Pratik Chaudhari, Manfred Morari:
BayesRace: Learning to race autonomously using prior experience. CoRL 2020: 1918-1929 - [c18]Guneet Singh Dhillon, Pratik Chaudhari, Avinash Ravichandran, Stefano Soatto:
A Baseline for Few-Shot Image Classification. ICLR 2020 - [c17]Rasool Fakoor, Pratik Chaudhari, Stefano Soatto, Alexander J. Smola:
Meta-Q-Learning. ICLR 2020 - [c16]Hao Li, Pratik Chaudhari, Hao Yang, Michael Lam, Avinash Ravichandran, Rahul Bhotika, Stefano Soatto:
Rethinking the Hyperparameters for Fine-tuning. ICLR 2020 - [c15]Yansong Gao, Pratik Chaudhari:
A Free-Energy Principle for Representation Learning. ICML 2020: 3367-3376 - [c14]Marco Maggipinto, Gian Antonio Susto, Pratik Chaudhari:
Proximal Deterministic Policy Gradient. IROS 2020: 5438-5444 - [c13]Rasool Fakoor, Jonas Mueller, Nick Erickson, Pratik Chaudhari, Alexander J. Smola:
Fast, Accurate, and Simple Models for Tabular Data via Augmented Distillation. NeurIPS 2020 - [i22]Hao Li, Pratik Chaudhari, Hao Yang, Michael Lam, Avinash Ravichandran, Rahul Bhotika, Stefano Soatto:
Rethinking the Hyperparameters for Fine-tuning. CoRR abs/2002.11770 (2020) - [i21]Yansong Gao, Pratik Chaudhari:
A Free-Energy Principle for Representation Learning. CoRR abs/2002.12406 (2020) - [i20]Rasool Fakoor, Pratik Chaudhari, Jonas Mueller, Alexander J. Smola:
TraDE: Transformers for Density Estimation. CoRR abs/2004.02441 (2020) - [i19]Achin Jain, Pratik Chaudhari, Manfred Morari:
BayesRace: Learning to race autonomously using prior experience. CoRR abs/2005.04755 (2020) - [i18]Rasool Fakoor, Jonas Mueller, Nick Erickson, Pratik Chaudhari, Alexander J. Smola:
Fast, Accurate, and Simple Models for Tabular Data via Augmented Distillation. CoRR abs/2006.14284 (2020) - [i17]Rasool Fakoor, Pratik Chaudhari, Alexander J. Smola:
DDPG++: Striving for Simplicity in Continuous-control Off-Policy Reinforcement Learning. CoRR abs/2006.15199 (2020) - [i16]Marco Maggipinto, Gian Antonio Susto, Pratik Chaudhari:
Proximal Deterministic Policy Gradient. CoRR abs/2008.00759 (2020) - [i15]Xiaoyi Chen, Pratik Chaudhari:
MIDAS: Multi-agent Interaction-aware Decision-making with Adaptive Strategies for Urban Autonomous Navigation. CoRR abs/2008.07081 (2020) - [i14]Yansong Gao, Pratik Chaudhari:
An Information-Geometric Distance on the Space of Tasks. CoRR abs/2011.00613 (2020) - [i13]Christopher D. Hsu, Heejin Jeong, George J. Pappas, Pratik Chaudhari:
Scalable Reinforcement Learning Policies for Multi-Agent Control. CoRR abs/2011.08055 (2020)
2010 – 2019
- 2019
- [c12]Rasool Fakoor, Pratik Chaudhari, Alexander J. Smola:
P3O: Policy-on Policy-off Policy Optimization. UAI 2019: 1017-1027 - [i12]Rasool Fakoor, Pratik Chaudhari, Alexander J. Smola:
P3O: Policy-on Policy-off Policy Optimization. CoRR abs/1905.01756 (2019) - [i11]Guneet S. Dhillon, Pratik Chaudhari, Avinash Ravichandran, Stefano Soatto:
A Baseline for Few-Shot Image Classification. CoRR abs/1909.02729 (2019) - [i10]Rasool Fakoor, Pratik Chaudhari, Stefano Soatto, Alexander J. Smola:
Meta-Q-Learning. CoRR abs/1910.00125 (2019) - [i9]Matteo Terzi, Gian Antonio Susto, Pratik Chaudhari:
Directional Adversarial Training for Cost Sensitive Deep Learning Classification Applications. CoRR abs/1910.03468 (2019) - [i8]Rita Fioresi, Pratik Chaudhari, Stefano Soatto:
A geometric interpretation of stochastic gradient descent using diffusion metrics. CoRR abs/1910.12194 (2019) - 2018
- [c11]Pratik Chaudhari, Stefano Soatto:
Stochastic gradient descent performs variational inference, converges to limit cycles for deep networks. ICLR (Poster) 2018 - [c10]Pratik Chaudhari, Stefano Soatto:
Stochastic Gradient Descent Performs Variational Inference, Converges to Limit Cycles for Deep Networks. ITA 2018: 1-10 - 2017
- [c9]Pratik Chaudhari, Adam M. Oberman, Stanley J. Osher, Stefano Soatto, Guillaume Carlier:
Partial differential equations for training deep neural networks. ACSSC 2017: 1627-1631 - [c8]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 - [i7]Pratik Chaudhari, Adam M. Oberman, Stanley J. Osher, Stefano Soatto, Guillaume Carlier:
Deep Relaxation: partial differential equations for optimizing deep neural networks. CoRR abs/1704.04932 (2017) - [i6]Pratik Chaudhari, Carlo Baldassi, Riccardo Zecchina, Stefano Soatto, Ameet Talwalkar:
Parle: parallelizing stochastic gradient descent. CoRR abs/1707.00424 (2017) - [i5]Pratik Chaudhari, Stefano Soatto:
Stochastic gradient descent performs variational inference, converges to limit cycles for deep networks. CoRR abs/1710.11029 (2017) - 2016
- [i4]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 abs/1611.01838 (2016) - 2015
- [i3]Pratik Chaudhari, Stefano Soatto:
Trivializing The Energy Landscape Of Deep Networks. CoRR abs/1511.06485 (2015) - 2014
- [c7]Pratik Chaudhari, Tichakorn Wongpiromsarn, Emilio Frazzoli:
Incremental minimum-violation control synthesis for robots interacting with external agents. ACC 2014: 1761-1768 - [c6]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: 1646-1651 - [c5]Valerio Varricchio, Pratik Chaudhari, Emilio Frazzoli:
Sampling-based algorithms for optimal motion planning using process algebra specifications. ICRA 2014: 5326-5332 - [i2]Minghui Zhu, Michael W. Otte, Pratik Chaudhari, Emilio Frazzoli:
Game theoretic controller synthesis for multi-robot motion planning Part I : Trajectory based algorithms. CoRR abs/1402.2708 (2014) - 2013
- [c4]Pratik Chaudhari, Sertac Karaman, David Hsu, Emilio Frazzoli:
Sampling-based algorithms for continuous-time POMDPs. ACC 2013: 4604-4610 - [c3]Luis I. Reyes Castro, Pratik Chaudhari, Jana Tumova, Sertac Karaman, Emilio Frazzoli, Daniela Rus:
Incremental sampling-based algorithm for minimum-violation motion planning. CDC 2013: 3217-3224 - [i1]Luis I. Reyes Castro, Pratik Chaudhari, Jana Tumova, Sertac Karaman, Emilio Frazzoli, Daniela Rus:
Incremental Sampling-based Algorithm for Minimum-violation Motion Planning. CoRR abs/1305.1102 (2013) - 2012
- [c2]Pratik Chaudhari, Sertac Karaman, Emilio Frazzoli:
Sampling-based algorithm for filtering using Markov chain approximations. CDC 2012: 5972-5978
2000 – 2009
- 2009
- [c1]Pratik Chaudhari:
Localization using Average Landmark Vector in the Presence of Clutter. NaBIC 2009: 1592-1595
Coauthor Index
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