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Pratik Chaudhari
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2020 – today
- 2024
- [c40]Siming He, Christopher D. Hsu, Dexter Ong, Yifei Simon Shao, Pratik Chaudhari:
Active Perception using Neural Radiance Fields. ACC 2024: 4353-4358 - [c39]Christopher D. Hsu, Mulugeta A. Haile, Pratik Chaudhari:
A Model for Multi-Agent Heterogeneous Interaction Problems. ACC 2024: 4637-4644 - [c38]Rasool Fakoor, Jonas Mueller, Zachary Chase Lipton, Pratik Chaudhari, Alex Smola:
Time-Varying Propensity Score to Bridge the Gap between the Past and Present. ICLR 2024 - [c37]Yifei Simon Shao, Yuwei Wu
, Laura Jarin-Lipschitz, Pratik Chaudhari, Vijay Kumar:
Design and Evaluation of Motion Planners for Quadrotors in Environments with Varying Complexities. ICRA 2024: 10033-10039 - [c36]Derek Cheng, Fernando Cladera Ojeda, Ankit Prabhu, Xu Liu, Alan Zhu, Patrick Corey Green, Reza Ehsani, Pratik Chaudhari, Vijay Kumar:
TreeScope: An Agricultural Robotics Dataset for LiDAR-Based Mapping of Trees in Forests and Orchards. ICRA 2024: 14860-14866 - [i65]Siming He, Yuezhan Tao, Igor Spasojevic, Vijay Kumar, Pratik Chaudhari:
An Active Perception Game for Robust Autonomous Exploration. CoRR abs/2404.00769 (2024) - [i64]Rohit Jena, Pratik Chaudhari, James C. Gee:
FireANTs: Adaptive Riemannian Optimization for Multi-Scale Diffeomorphic Registration. CoRR abs/2404.01249 (2024) - [i63]Matteo Marchi, Stefano Soatto, Pratik Chaudhari, Paulo Tabuada:
Heat Death of Generative Models in Closed-Loop Learning. CoRR abs/2404.02325 (2024) - [i62]Siming He, Zach Osman, Pratik Chaudhari:
From NeRFs to Gaussian Splats, and Back. CoRR abs/2405.09717 (2024) - [i61]Tian Yu Liu, Stefano Soatto, Matteo Marchi, Pratik Chaudhari, Paulo Tabuada:
Meanings and Feelings of Large Language Models: Observability of Latent States in Generative AI. CoRR abs/2405.14061 (2024) - [i60]Rohit Jena, Pratik Chaudhari, James C. Gee:
Deep Implicit Optimization for Robust and Flexible Image Registration. CoRR abs/2406.07361 (2024) - [i59]Christopher D. Hsu, Pratik Chaudhari:
Active Scout: Multi-Target Tracking Using Neural Radiance Fields in Dense Urban Environments. CoRR abs/2406.07431 (2024) - [i58]Yuwei Wu, Igor Spasojevic, Pratik Chaudhari, Vijay Kumar:
Optimal Convex Cover as Collision-free Space Approximation for Trajectory Generation. CoRR abs/2406.09631 (2024) - [i57]Xu Liu, Jiuzhou Lei, Ankit Prabhu, Yuezhan Tao, Igor Spasojevic, Pratik Chaudhari, Nikolay Atanasov, Vijay Kumar:
SlideSLAM: Sparse, Lightweight, Decentralized Metric-Semantic SLAM for Multi-Robot Navigation. CoRR abs/2406.17249 (2024) - [i56]Rahul Ramesh, Anthony Bisulco, Ronald W. Ditullio, Linran Wei, Vijay Balasubramanian, Kostas Daniilidis, Pratik Chaudhari:
Many Perception Tasks are Highly Redundant Functions of their Input Data. CoRR abs/2407.13841 (2024) - [i55]Rohit Jena, Deeksha Sethi, Pratik Chaudhari, James C. Gee:
Deep Learning in Medical Image Registration: Magic or Mirage? CoRR abs/2408.05839 (2024) - [i54]Yan Sun, Pratik Chaudhari, Ian J. Barnett, Edgar Dobriban:
A Confidence Interval for the ℓ2 Expected Calibration Error. CoRR abs/2408.08998 (2024) - [i53]Yifei Simon Shao, Tianyu Li, Shafagh Keyvanian, Pratik Chaudhari, Vijay Kumar, Nadia Figueroa:
Constraint-Aware Intent Estimation for Dynamic Human-Robot Object Co-Manipulation. CoRR abs/2409.00215 (2024) - [i52]Yuezhan Tao, Dexter Ong, Varun Murali, Igor Spasojevic, Pratik Chaudhari, Vijay Kumar:
RT-GuIDE: Real-Time Gaussian splatting for Information-Driven Exploration. CoRR abs/2409.18122 (2024) - [i51]Jiuzhou Lei, Ankit Prabhu, Xu Liu, Fernando Cladera Ojeda, Mehrad Mortazavi, Reza Ehsani, Pratik Chaudhari, Vijay Kumar:
4D Metric-Semantic Mapping for Persistent Orchard Monitoring: Method and Dataset. CoRR abs/2409.19786 (2024) - 2023
- [j7]Ronald W. Ditullio, Chetan Parthiban, Eugenio Piasini, Pratik Chaudhari, Vijay Balasubramanian, Yale E. Cohen:
Time as a supervisor: temporal regularity and auditory object learning. Frontiers Comput. Neurosci. 17 (2023) - [c35]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 Charles, Archana Venkataraman, Brian Caffo, Javier J. How, Justus M. Kebschull, John W. Krakauer, Maxim Bichuch, Kaleab Alemayehu Kinfu, Eva Yezerets, Dinesh Jayaraman
Prospective Learning: Principled Extrapolation to the Future. CoLLAs 2023: 347-357 - [c34]Rohit Jena, Lukas Zhornyak, Nehal Doiphode, Pratik Chaudhari, Vivek Buch
Beyond mAP: Towards Better Evaluation of Instance Segmentation. CVPR 2023: 11309-11318 - [c33]Ashwin De Silva, Rahul Ramesh, Carey E. Priebe, Pratik Chaudhari, Joshua T. Vogelstein:
The Value of Out-of-Distribution Data. ICML 2023: 7366-7389 - [c32]Rahul Ramesh, Jialin Mao, Itay Griniasty, Rubing Yang, Han Kheng Teoh, Mark K. Transtrum, James P. Sethna, Pratik Chaudhari:
A Picture of the Space of Typical Learnable Tasks. ICML 2023: 28680-28700 - [c31]Yao Liu, Pratik Chaudhari, Rasool Fakoor:
Budgeting Counterfactual for Offline RL. NeurIPS 2023 - [c30]Shiyun Xu, Zhiqi Bu, Pratik Chaudhari, Ian J. Barnett:
Sparse Neural Additive Model: Interpretable Deep Learning with Feature Selection via Group Sparsity. ECML/PKDD (3) 2023: 343-359 - [i50]Rohit Jena, Pratik Chaudhari, James C. Gee, Ganesh Subramanian Iyer, Siddharth Choudhary, Brandon M. Smith:
Mesh Strikes Back: Fast and Efficient Human Reconstruction from RGB videos. CoRR abs/2303.08808 (2023) - [i49]Yansong Gao, Zhihong Pan, Xin Zhou, Le Kang, Pratik Chaudhari:
Fast Diffusion Probabilistic Model Sampling through the lens of Backward Error Analysis. CoRR abs/2304.11446 (2023) - [i48]Jialin Mao, Itay Griniasty, Han Kheng Teoh, Rahul Ramesh, Rubing Yang, Mark K. Transtrum, James P. Sethna, Pratik Chaudhari:
The Training Process of Many Deep Networks Explores the Same Low-Dimensional Manifold. CoRR abs/2305.01604 (2023) - [i47]Daiwei Chen, Weikai Chang, Pratik Chaudhari:
Learning Capacity: A Measure of the Effective Dimensionality of a Model. CoRR abs/2305.17332 (2023) - [i46]Stefano Soatto, Paulo Tabuada, Pratik Chaudhari, Tian Yu Liu:
Taming AI Bots: Controllability of Neural States in Large Language Models. CoRR abs/2305.18449 (2023) - [i45]Yao Liu, Pratik Chaudhari, Rasool Fakoor:
Budgeting Counterfactual for Offline RL. CoRR abs/2307.06328 (2023) - [i44]Rongguang Wang, Güray Erus, Pratik Chaudhari, Christos Davatzikos:
Adapting Machine Learning Diagnostic Models to New Populations Using a Small Amount of Data: Results from Clinical Neuroscience. CoRR abs/2308.03175 (2023) - [i43]Xiwen Liu, Keshava Katti, Yunfei He, Paul Jacob, Claudia Richter, Uwe Schroeder, Santosh Kurinec, Pratik Chaudhari, Deep Jariwala:
Analog Content-Addressable Memory from Complementary FeFETs. CoRR abs/2309.09165 (2023) - [i42]Yifei Simon Shao, Yuwei Wu, Laura Jarin-Lipschitz, Pratik Chaudhari, Vijay Kumar:
Design and Evaluation of Motion Planners for Quadrotors. CoRR abs/2309.13720 (2023) - [i41]Derek Cheng, Fernando Cladera Ojeda, Ankit Prabhu, Xu Liu, Alan Zhu, Patrick Corey Green, Reza Ehsani, Pratik Chaudhari, Vijay Kumar:
TreeScope: An Agricultural Robotics Dataset for LiDAR-Based Mapping of Trees in Forests and Orchards. CoRR abs/2310.02162 (2023) - [i40]Siming He, Christopher D. Hsu, Dexter Ong, Yifei Simon Shao, Pratik Chaudhari:
Active Perception using Neural Radiance Fields. CoRR abs/2310.09892 (2023) - [i39]Rohit Jena, Ganesh Subramanian Iyer, Siddharth Choudhary, Brandon M. Smith, Pratik Chaudhari, James C. Gee:
SplatArmor: Articulated Gaussian splatting for animatable humans from monocular RGB videos. CoRR abs/2311.10812 (2023) - [i38]Haoran Tang, Xin Zhou, Jieren Deng, Zhihong Pan, Hao Tian, Pratik Chaudhari:
Retrieving Conditions from Reference Images for Diffusion Models. CoRR abs/2312.02521 (2023) - 2022
- [j6]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) - [c29]Anirudh Cowlagi, Pratik Chaudhari:
Does the Geometry of the Data Control the Geometry of Neural Predictions? (Student Abstract). AAAI 2022: 12931-12932 - [c28]Rahul Ramesh, Pratik Chaudhari:
Model Zoo: A Growing Brain That Learns Continually. ICLR 2022 - [c27]Yansong Gao, Rahul Ramesh, Pratik Chaudhari:
Deep Reference Priors: What is the best way to pretrain a model? ICML 2022: 7036-7051 - [c26]Rubing Yang, Jialin Mao, Pratik Chaudhari:
Does the Data Induce Capacity Control in Deep Learning? ICML 2022: 25166-25197 - [i37]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, 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 L. Platt, Lyle H. 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) - [i36]Yansong Gao, Rahul Ramesh, Pratik Chaudhari:
Deep Reference Priors: What is the best way to pretrain a model? CoRR abs/2202.00187 (2022) - [i35]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) - [i34]Rongguang Wang, Pratik Chaudhari, Christos Davatzikos:
Machine Learning Models Are Not Necessarily Biased When Constructed Properly: Evidence from Neuroimaging Studies. CoRR abs/2205.13421 (2022) - [i33]Keshava Katti
MammoDL: Mammographic Breast Density Estimation using Federated Learning. CoRR abs/2206.05575 (2022) - [i32]Christopher D. Hsu, Mulugeta A. Haile, Pratik Chaudhari:
A Model for Perimeter-Defense Problems with Heterogeneous Teams. CoRR abs/2208.01430 (2022) - [i31]Ashwin De Silva, Rahul Ramesh, Carey E. Priebe, Pratik Chaudhari, Joshua T. Vogelstein:
The Value of Out-of-Distribution Data. CoRR abs/2208.10967 (2022) - [i30]Rasool Fakoor, Jonas Mueller, Zachary C. Lipton, Pratik Chaudhari, Alexander J. Smola:
Data drift correction via time-varying importance weight estimator. CoRR abs/2210.01422 (2022) - [i29]Rahul Ramesh, Jialin Mao, Itay Griniasty, Rubing Yang, Han Kheng Teoh, Mark K. Transtrum, James P. Sethna, Pratik Chaudhari:
A picture of the space of typical learnable tasks. CoRR abs/2210.17011 (2022) - 2021
- [j5]Yansong Gao, Pratik Chaudhari
A free-energy principle for representation learning. Mach. Learn. Sci. Technol. 2(4): 45004 (2021) - [j4]Ty Nguyen
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
Scalable Reinforcement Learning Policies for Multi-Agent Control. IROS 2021: 4785-4791 - [c21]Rongguang Wang
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
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
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
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
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
Alexander J. Smola
aka: Alex Smola
aka: Alex Smola
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