Pratik Chaudhari

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Stefano SoattoProfessor of Computer Science, UCLA; VP, AWSVerified email at ucla.edu
Alex SmolaBoson AIVerified email at smola.org
Rasool FakoorAmazon Web ServicesVerified email at amazon.com
Christos DavatzikosDirector, AI2D Center for AI/Data Science for Integrated Diagnostics, Professor Radiology/ESE/DBEIVerified email at pennmedicine.upenn.edu
Emilio FrazzoliProfessor of Dynamic Systems and ControlVerified email at ethz.ch
Zachary C. LiptonProfessor of Machine Learning at Carnegie Mellon; CTO / CSO at AbridgeVerified email at cmu.edu
Riccardo Zecchinaprofessor, theoretical physics, Bocconi UniversityVerified email at unibocconi.it
Carlo BaldassiBocconi University; ELLIS scholarVerified email at unibocconi.it
Rongguang WangUniversity of PennsylvaniaVerified email at seas.upenn.edu
Avinash RavichandranPrincipal Applied Scientist, Perception, CruiseVerified email at cis.jhu.edu
Aston ZhangGenAI, MetaVerified email at meta.com
Mu LiAmazonVerified email at amazon.com
Adam M. ObermanProfessor, Department of Mathematics and Statistics, McGill UniversityVerified email at mcgill.ca
Anna ChoromanskaNew York UniversityVerified email at nyu.edu
Yann LeCunChief AI Scientist at Facebook & Silver Professor at the Courant Institute, New York UniversityVerified email at cs.nyu.edu
Levent SagunFAIRVerified email at meta.com
Jennifer ChayesProfessor, UC BerkeleyVerified email at jenniferchayes.com
Christian BorgsProfessor, UC BerkeleyVerified email at christianborgs.com
Rahul RameshUniversity of PennsylvaniaVerified email at seas.upenn.edu
Sertac KaramanProfessor of Aeronautics and Astronautics, Massachusetts Institute of TechnologyVerified email at mit.edu

Pratik Chaudhari

University of Pennsylvania

Verified email at seas.upenn.edu - Homepage

Deep Learning Machine Learning Robotics Computer Vision


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Dive into deep learning A Zhang, Z Lipton, Li, Mu, AJ Smola	909	2021
Entropy-SGD: Biasing gradient descent into wide valleys P Chaudhari, A Choromanska, S Soatto, Y LeCun, C Baldassi, C Borgs, ... Journal of Statistical Mechanics: Theory and Experiment 2019 (12), 124018, 2019	710	2019
Entropy-SGD: biasing gradient descent into wide valleys P Chaudhari, A Choromanska, S Soatto, Y LeCun, C Baldassi, C Borgs, ... ICLR, arXiv:1611.01838, 2017	710	2017
A Baseline for Few-Shot Image Classification GS Dhillon, P Chaudhari, A Ravichandran, S Soatto ICLR, arXiv:1909.02729, 2020	548	2020
Stochastic gradient descent performs variational inference, converges to limit cycles for deep networks P Chaudhari, S Soatto ICLR, arXiv:1710.11029, 2018	300	2018
Deep relaxation: partial differential equations for optimizing deep neural networks P Chaudhari, A Oberman, S Osher, S Soatto, G Carlier Research in the Mathematical Sciences 5, 1-30, 2018	159	2018
Meta-Q-Learning R Fakoor, P Chaudhari, S Soatto, AJ Smola ICLR, arXiv:1910.00125, 2020	139	2020
Rethinking the Hyperparameters for Fine-tuning H Li, P Chaudhari, H Yang, M Lam, A Ravichandran, R Bhotika, S Soatto ICLR, arXiv:2002.11770, 2020	103	2020
Incremental sampling-based algorithm for minimum-violation motion planning LIR Castro, P Chaudhari, J Tůmová, S Karaman, E Frazzoli, D Rus CDC, 3217-3224, 2013	100	2013
Fast, Accurate, and Simple Models for Tabular Data via Augmented Distillation R Fakoor, J Mueller, N Erickson, P Chaudhari, AJ Smola NeurIPS, arXiv:2006.14284, 2020	48	2020
P3O: Policy-on Policy-off Policy Optimization R Fakoor, P Chaudhari, AJ Smola UAI, arXiv:1905.01756, 2019	47	2019
Sampling-based algorithms for continuous-time POMDPs P Chaudhari, S Karaman, D Hsu, E Frazzoli ACC, 4604-4610, 2013	39	2013
Embracing the Disharmony in Medical Imaging: A Simple and Effective Framework for Domain Adaptation R Wang, P Chaudhari, C Davatzikos Medical Image Analysis, arXiv:2103.12857, 2021	36	2021
Model Zoo: A Growing "Brain" That Learns Continually R Ramesh, P Chaudhari ICLR, arXiv:2106.03027, 2022	34*	2022
On the energy landscape of deep networks P Chaudhari, S Soatto ICML Workshop on Optimization in Machine Learning, 2016	31*	2016
Game theoretic controller synthesis for multi-robot motion planning Part I: Trajectory based algorithms M Zhu, M Otte, P Chaudhari, E Frazzoli ICRA, 1646-1651, 2014	29	2014
Parle: parallelizing stochastic gradient descent P Chaudhari, C Baldassi, R Zecchina, S Soatto, A Talwalkar, A Oberman SysML, arXiv:1707.00424, 2018	25	2018
BayesRace: Learning to race autonomously using prior experience A Jain, P Chaudhari, M Morari CoRL, arXiv:2005.04755, 2020	24	2020
Harmonization with Flow-based Causal Inference R Wang, P Chaudhari, C Davatzikos MICCAI, arXiv:2106.06845, 2021	22	2021
Sampling-based algorithms for optimal motion planning using process algebra specifications V Varricchio, P Chaudhari, E Frazzoli ICRA, 5326-5332, 2014	20	2014

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