Pratik Chaudhari - Google Scholar Citations

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Stefano SoattoProfessor of Computer Science, UCLAVerified email at ucla.edu
Emilio FrazzoliProfessor of Dynamic Systems and ControlVerified email at ethz.ch
Riccardo Zecchinaprofessor, theoretical physics, Bocconi UniversityVerified email at unibocconi.it
Carlo BaldassiBocconi University; INFNVerified email at unibocconi.it
Sertac KaramanAssociate Professor of Aeronautics and Astronautics, Massachusetts Institute of TechnologyVerified email at mit.edu
Adam M. ObermanProfessor, Department of Mathematics and Statistics, McGill UniversityVerified email at mcgill.ca
Anna ChoromanskaNew York UniversityVerified email at cims.nyu.edu
Yann LeCunChief AI Scientist at Facebook & Silver Professor at the Courant Institute, New York UniversityVerified email at cs.nyu.edu
Levent SagunEPFLVerified email at epfl.ch
Jennifer ChayesTechnical Fellow & Managing Director, MicrosoftVerified email at microsoft.com
Christian BorgsPrincipal Researcher, Microsoft ResearchVerified email at microsoft.com
S osherVerified email at math.ucla.edu
Daniela RusAndrew (1956) and Erna Viterbi Professor of Computer Science, MITVerified email at csail.mit.edu
Jana TumovaKTHVerified email at kth.se
David HsuProfessor of Computer Science, National University of SingaporeVerified email at comp.nus.edu.sg
Michael OtteAssistant Professor, University of Maryland College ParkVerified email at umd.edu
Minghui ZhuAssociate Professor, Electrical Engineering and Computer Science, Pennsylvania State UniversityVerified email at psu.edu
Ameet TalwalkarCMU and Determined AIVerified email at cmu.edu
Valerio VarricchioMassachusetts Institute of TechnologyVerified email at mit.edu
Avinash RavichandranAWSVerified email at cis.jhu.edu

Pratik Chaudhari

University of Pennsylvania

Verified email at ucla.edu - Homepage

Neural Networks Machine Learning Robotics Motion Planning


Title	Cited by	Year
Entropy-SGD: biasing gradient descent into wide valleys P Chaudhari, A Choromanska, S Soatto, Y LeCun, C Baldassi, C Borgs, ... arXiv preprint arXiv:1611.01838, 2016	214	2016
Stochastic gradient descent performs variational inference, converges to limit cycles for deep networks P Chaudhari, S Soatto 2018 Information Theory and Applications Workshop (ITA), 1-10, 2018	81	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 (3), 30, 2018	58	2018
Incremental sampling-based algorithm for minimum-violation motion planning LIR Castro, P Chaudhari, J Tůmová, S Karaman, E Frazzoli, D Rus 52nd IEEE Conference on Decision and Control, 3217-3224, 2013	53	2013
Sampling-based algorithms for continuous-time POMDPs P Chaudhari, S Karaman, D Hsu, E Frazzoli 2013 American Control Conference, 4604-4610, 2013	23	2013
On the energy landscape of deep networks P Chaudhari, S Soatto arXiv:1511.06485, 2015	20*	2015
Parle: parallelizing stochastic gradient descent P Chaudhari, C Baldassi, R Zecchina, S Soatto, A Talwalkar, A Oberman arXiv preprint arXiv:1707.00424, 2017	14	2017
Game theoretic controller synthesis for multi-robot motion planning Part I: Trajectory based algorithms M Zhu, M Otte, P Chaudhari, E Frazzoli 2014 IEEE International Conference on Robotics and Automation (ICRA), 1646-1651, 2014	14	2014
Sampling-based algorithms for optimal motion planning using process algebra specifications V Varricchio, P Chaudhari, E Frazzoli 2014 IEEE International Conference on Robotics and Automation (ICRA), 5326-5332, 2014	12	2014
Incremental minimum-violation control synthesis for robots interacting with external agents P Chaudhari, T Wongpiromsarny, E Frazzoli 2014 American Control Conference, 1761-1768, 2014	6	2014
Sampling-based algorithm for filtering using Markov chain approximations P Chaudhari, S Karaman, E Frazzoli 2012 IEEE 51st IEEE Conference on Decision and Control (CDC), 5972-5978, 2012	5	2012
Meta-Q-Learning R Fakoor, P Chaudhari, S Soatto, AJ Smola arXiv preprint arXiv:1910.00125, 2019	2*	2019
A Baseline for Few-Shot Image Classification GS Dhillon, P Chaudhari, A Ravichandran, S Soatto arXiv preprint arXiv:1909.02729, 2019	2	2019
Localization using Average Landmark Vector in the presence of clutter P Chaudhari 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC …, 2009	2	2009
P3O: Policy-on Policy-off Policy Optimization R Fakoor, P Chaudhari, AJ Smola arXiv preprint arXiv:1905.01756, 2019	1	2019
A geometric interpretation of stochastic gradient descent using diffusion metrics R Fioresi, P Chaudhari, S Soatto arXiv preprint arXiv:1910.12194, 2019		2019
Directional Adversarial Training for Cost Sensitive Deep Learning Classification Applications M Terzi, GA Susto, P Chaudhari arXiv preprint arXiv:1910.03468, 2019		2019
Approximate POMDP homomorphisms P Chaudhari		2014
Algorithms for autonomous urban navigation with formal specifications P Chaudhari Massachusetts Institute of Technology, 2014		2014
Incremental sampling based algorithms for state estimation P Chaudhari Massachusetts Institute of Technology, 2012		2012

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