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2020 – today
- 2023
[j1]Minyoung Huh, Hossein Mobahi, Richard Zhang, Brian Cheung, Pulkit Agrawal, Phillip Isola:
The Low-Rank Simplicity Bias in Deep Networks. Trans. Mach. Learn. Res. 2023 (2023)- [i51]Andreea Bobu, Andi Peng, Pulkit Agrawal, Julie Shah, Anca D. Dragan:
Aligning Robot and Human Representations. CoRR abs/2302.01928 (2023) - [i50]Baxi Chong, Di Luo, Tianyu Wang, Gabriel Margolis, Juntao He, Pulkit Agrawal, Marin Soljacic, Daniel I. Goldman:
Geometry of contact: contact planning for multi-legged robots via spin models duality. CoRR abs/2302.03019 (2023) - [i49]Max Simchowitz, Anurag Ajay, Pulkit Agrawal, Akshay Krishnamurthy:
Statistical Learning under Heterogenous Distribution Shift. CoRR abs/2302.13934 (2023) - [i48]Sameer Pai, Tao Chen, Megha Tippur, Edward H. Adelson, Abhishek Gupta, Pulkit Agrawal:
TactoFind: A Tactile Only System for Object Retrieval. CoRR abs/2303.13482 (2023) - [i47]Ligong Han, Seungwook Han, Shivchander Sudalairaj, Charlotte Loh, Rumen Dangovski, Fei Deng, Pulkit Agrawal, Dimitris N. Metaxas, Leonid Karlinsky, Tsui-Wei Weng, Akash Srivastava:
Constructive Assimilation: Boosting Contrastive Learning Performance through View Generation Strategies. CoRR abs/2304.00601 (2023) - [i46]Yandong Ji, Gabriel B. Margolis, Pulkit Agrawal:
DribbleBot: Dynamic Legged Manipulation in the Wild. CoRR abs/2304.01159 (2023) - [i45]Aviv Netanyahu, Abhishek Gupta, Max Simchowitz, Kaiqing Zhang, Pulkit Agrawal:
Learning to Extrapolate: A Transductive Approach. CoRR abs/2304.14329 (2023) - [i44]Minyoung Huh, Brian Cheung, Pulkit Agrawal, Phillip Isola:
Straightening Out the Straight-Through Estimator: Overcoming Optimization Challenges in Vector Quantized Networks. CoRR abs/2305.08842 (2023) - [i43]Boyuan Chen, Chuning Zhu, Pulkit Agrawal, Kaiqing Zhang, Abhishek Gupta:
Self-Supervised Reinforcement Learning that Transfers using Random Features. CoRR abs/2305.17250 (2023) - 2022
- [c48]Gabriel B. Margolis, Pulkit Agrawal:
Walk These Ways: Tuning Robot Control for Generalization with Multiplicity of Behavior. CoRL 2022: 22-31 - [c47]Anthony Simeonov, Yilun Du, Yen-Chen Lin, Alberto Rodriguez Garcia, Leslie Pack Kaelbling, Tomás Lozano-Pérez, Pulkit Agrawal:
SE(3)-Equivariant Relational Rearrangement with Neural Descriptor Fields. CoRL 2022: 835-846 - [c46]Jie Xu, Sangwoon Kim, Tao Chen, Alberto Rodriguez Garcia, Pulkit Agrawal, Wojciech Matusik, Shinjiro Sueda:
Efficient Tactile Simulation with Differentiability for Robotic Manipulation. CoRL 2022: 1488-1498 - [c45]Rumen Dangovski, Li Jing, Charlotte Loh, Seungwook Han, Akash Srivastava, Brian Cheung, Pulkit Agrawal, Marin Soljacic:
Equivariant Self-Supervised Learning: Encouraging Equivariance in Representations. ICLR 2022 - [c44]Zhang-Wei Hong, Tao Chen, Yen-Chen Lin, Joni Pajarinen, Pulkit Agrawal:
Topological Experience Replay. ICLR 2022 - [c43]Zhang-Wei Hong, Ge Yang, Pulkit Agrawal:
Bi-linear Value Networks for Multi-goal Reinforcement Learning. ICLR 2022 - [c42]Ge Yang, Anurag Ajay, Pulkit Agrawal:
Overcoming The Spectral Bias of Neural Value Approximation. ICLR 2022 - [c41]Dibya Ghosh, Anurag Ajay, Pulkit Agrawal, Sergey Levine:
Offline RL Policies Should Be Trained to be Adaptive. ICML 2022: 7513-7530 - [c40]Aviv Netanyahu, Tianmin Shu, Joshua B. Tenenbaum, Pulkit Agrawal:
Discovering Generalizable Spatial Goal Representations via Graph-based Active Reward Learning. ICML 2022: 16480-16495 - [c39]Lara Zlokapa, Yiyue Luo, Jie Xu, Michael Foshey, Kui Wu, Pulkit Agrawal, Wojciech Matusik:
An Integrated Design Pipeline for Tactile Sensing Robotic Manipulators. ICRA 2022: 3136-3142 - [c38]Richard Li, Carlos Esteves, Ameesh Makadia, Pulkit Agrawal:
Stable Object Reorientation using Contact Plane Registration. ICRA 2022: 6379-6385 - [c37]Anthony Simeonov, Yilun Du, Andrea Tagliasacchi, Joshua B. Tenenbaum, Alberto Rodriguez, Pulkit Agrawal, Vincent Sitzmann:
Neural Descriptor Fields: SE(3)-Equivariant Object Representations for Manipulation. ICRA 2022: 6394-6400 - [c36]Haokuan Luo, Albert Yue, Zhang-Wei Hong, Pulkit Agrawal:
Stubborn: A Strong Baseline for Indoor Object Navigation. IROS 2022: 3287-3293 - [c35]Anurag Ajay, Abhishek Gupta, Dibya Ghosh, Sergey Levine, Pulkit Agrawal:
Distributionally Adaptive Meta Reinforcement Learning. NeurIPS 2022 - [c34]Eric Chen, Zhang-Wei Hong, Joni Pajarinen, Pulkit Agrawal:
Redeeming intrinsic rewards via constrained optimization. NeurIPS 2022 - [i42]Haokuan Luo, Albert Yue, Zhang-Wei Hong, Pulkit Agrawal:
Stubborn: A Strong Baseline for Indoor Object Navigation. CoRR abs/2203.07359 (2022) - [i41]Zhang-Wei Hong, Tao Chen, Yen-Chen Lin, Joni Pajarinen, Pulkit Agrawal:
Topological Experience Replay. CoRR abs/2203.15845 (2022) - [i40]Lara Zlokapa, Yiyue Luo, Jie Xu, Michael Foshey, Kui Wu, Pulkit Agrawal, Wojciech Matusik:
An Integrated Design Pipeline for Tactile Sensing Robotic Manipulators. CoRR abs/2204.07149 (2022) - [i39]Zhang-Wei Hong, Ge Yang, Pulkit Agrawal:
Bilinear value networks. CoRR abs/2204.13695 (2022) - [i38]Gabriel B. Margolis, Ge Yang, Kartik Paigwar, Tao Chen, Pulkit Agrawal:
Rapid Locomotion via Reinforcement Learning. CoRR abs/2205.02824 (2022) - [i37]Ge Yang, Anurag Ajay, Pulkit Agrawal:
Overcoming the Spectral Bias of Neural Value Approximation. CoRR abs/2206.04672 (2022) - [i36]Dibya Ghosh, Anurag Ajay, Pulkit Agrawal, Sergey Levine:
Offline RL Policies Should be Trained to be Adaptive. CoRR abs/2207.02200 (2022) - [i35]Richard Li, Carlos Esteves, Ameesh Makadia, Pulkit Agrawal:
Stable Object Reorientation using Contact Plane Registration. CoRR abs/2208.08962 (2022) - [i34]Anurag Ajay, Abhishek Gupta, Dibya Ghosh, Sergey Levine, Pulkit Agrawal:
Distributionally Adaptive Meta Reinforcement Learning. CoRR abs/2210.03104 (2022) - [i33]Eric Chen, Zhang-Wei Hong, Joni Pajarinen, Pulkit Agrawal:
Redeeming Intrinsic Rewards via Constrained Optimization. CoRR abs/2211.07627 (2022) - [i32]Anthony Simeonov, Yilun Du, Yen-Chen Lin, Alberto Rodriguez, Leslie Pack Kaelbling, Tomás Lozano-Pérez, Pulkit Agrawal:
SE(3)-Equivariant Relational Rearrangement with Neural Descriptor Fields. CoRR abs/2211.09786 (2022) - [i31]Tao Chen, Megha Tippur, Siyang Wu, Vikash Kumar, Edward H. Adelson, Pulkit Agrawal:
Visual Dexterity: In-hand Dexterous Manipulation from Depth. CoRR abs/2211.11744 (2022) - [i30]Aviv Netanyahu, Tianmin Shu, Joshua B. Tenenbaum, Pulkit Agrawal:
Discovering Generalizable Spatial Goal Representations via Graph-based Active Reward Learning. CoRR abs/2211.15339 (2022) - [i29]Anurag Ajay, Yilun Du, Abhi Gupta, Joshua B. Tenenbaum, Tommi S. Jaakkola, Pulkit Agrawal:
Is Conditional Generative Modeling all you need for Decision-Making? CoRR abs/2211.15657 (2022) - [i28]Gabriel B. Margolis, Pulkit Agrawal:
Walk These Ways: Tuning Robot Control for Generalization with Multiplicity of Behavior. CoRR abs/2212.03238 (2022) - 2021
- [c33]Pooya Khorrami, Olga Simek, Brian Cheung, Mark Veillette, Rumen Dangovski, Ileana Rugina, Marin Soljacic, Pulkit Agrawal:
Adapting Deep Learning Models to New Meteorological Contexts Using Transfer Learning. IEEE BigData 2021: 4169-4177 - [c32]Yunzhu Li, Shuang Li, Vincent Sitzmann, Pulkit Agrawal, Antonio Torralba:
3D Neural Scene Representations for Visuomotor Control. CoRL 2021: 112-123 - [c31]Tao Chen, Jie Xu, Pulkit Agrawal:
A System for General In-Hand Object Re-Orientation. CoRL 2021: 297-307 - [c30]Gabriel B. Margolis, Tao Chen, Kartik Paigwar, Xiang Fu, Donghyun Kim, Sangbae Kim, Pulkit Agrawal:
Learning to Jump from Pixels. CoRL 2021: 1025-1034 - [c29]Pulkit Agrawal:
The Task Specification Problem. CoRL 2021: 1745-1751 - [c28]Anurag Ajay, Aviral Kumar, Pulkit Agrawal, Sergey Levine, Ofir Nachum:
OPAL: Offline Primitive Discovery for Accelerating Offline Reinforcement Learning. ICLR 2021 - [c27]Xiang Fu, Ge Yang, Pulkit Agrawal, Tommi S. Jaakkola:
Learning Task Informed Abstractions. ICML 2021: 3480-3491 - [c26]Joshua Gruenstein, Tao Chen, Neel Doshi, Pulkit Agrawal:
Residual Model Learning for Microrobot Control. ICRA 2021: 7219-7226 - [c25]Jie Xu, Tao Chen, Lara Zlokapa, Michael Foshey, Wojciech Matusik, Shinjiro Sueda, Pulkit Agrawal:
An End-to-End Differentiable Framework for Contact-Aware Robot Design. Robotics: Science and Systems 2021 - [i27]Minyoung Huh, Hossein Mobahi, Richard Zhang, Brian Cheung, Pulkit Agrawal, Phillip Isola:
The Low-Rank Simplicity Bias in Deep Networks. CoRR abs/2103.10427 (2021) - [i26]Joshua Gruenstein, Tao Chen, Neel Doshi, Pulkit Agrawal:
Residual Model Learning for Microrobot Control. CoRR abs/2104.00631 (2021) - [i25]Xiang Fu, Ge Yang, Pulkit Agrawal, Tommi S. Jaakkola:
Learning Task Informed Abstractions. CoRR abs/2106.15612 (2021) - [i24]Yunzhu Li, Shuang Li, Vincent Sitzmann, Pulkit Agrawal, Antonio Torralba:
3D Neural Scene Representations for Visuomotor Control. CoRR abs/2107.04004 (2021) - [i23]Jie Xu, Tao Chen, Lara Zlokapa, Michael Foshey, Wojciech Matusik, Shinjiro Sueda, Pulkit Agrawal:
An End-to-End Differentiable Framework for Contact-Aware Robot Design. CoRR abs/2107.07501 (2021) - [i22]Gabriel B. Margolis, Tao Chen, Kartik Paigwar, Xiang Fu, Donghyun Kim, Sangbae Kim, Pulkit Agrawal:
Learning to Jump from Pixels. CoRR abs/2110.15344 (2021) - [i21]Rumen Dangovski, Li Jing, Charlotte Loh, Seungwook Han, Akash Srivastava, Brian Cheung, Pulkit Agrawal, Marin Soljacic:
Equivariant Contrastive Learning. CoRR abs/2111.00899 (2021) - [i20]Tao Chen, Jie Xu, Pulkit Agrawal:
A System for General In-Hand Object Re-Orientation. CoRR abs/2111.03043 (2021) - [i19]Anthony Simeonov, Yilun Du, Andrea Tagliasacchi, Joshua B. Tenenbaum, Alberto Rodriguez, Pulkit Agrawal, Vincent Sitzmann:
Neural Descriptor Fields: SE(3)-Equivariant Object Representations for Manipulation. CoRR abs/2112.05124 (2021) - 2020
- [c24]Eliza Kosoy, Jasmine Collins, David M. Chan, Deepak Pathak, Pulkit Agrawal, Alison Gopnik:
Exploring Exploration: Comparing Children with Agents in Unified Exploration Environments. CogSci 2020 - [c23]Anthony Simeonov, Yilun Du, Beomjoon Kim, Francois Robert Hogan, Joshua B. Tenenbaum, Pulkit Agrawal, Alberto Rodriguez:
A Long Horizon Planning Framework for Manipulating Rigid Pointcloud Objects. CoRL 2020: 1582-1601 - [c22]Tyler B. Johnson, Pulkit Agrawal, Haijie Gu, Carlos Guestrin:
AdaScale SGD: A User-Friendly Algorithm for Distributed Training. ICML 2020: 4911-4920 - [c21]Richard Li, Allan Jabri, Trevor Darrell, Pulkit Agrawal:
Towards Practical Multi-Object Manipulation using Relational Reinforcement Learning. ICRA 2020: 4051-4058 - [i18]Tyler B. Johnson, Pulkit Agrawal, Haijie Gu, Carlos Guestrin:
AdaScale SGD: A User-Friendly Algorithm for Distributed Training. CoRR abs/2007.05105 (2020) - [i17]Anurag Ajay, Aviral Kumar, Pulkit Agrawal, Sergey Levine, Ofir Nachum:
OPAL: Offline Primitive Discovery for Accelerating Offline Reinforcement Learning. CoRR abs/2010.13611 (2020) - [i16]Anthony Simeonov, Yilun Du, Beomjoon Kim, Francois Robert Hogan, Joshua B. Tenenbaum, Pulkit Agrawal, Alberto Rodriguez:
A Long Horizon Planning Framework for Manipulating Rigid Pointcloud Objects. CoRR abs/2011.08177 (2020)
2010 – 2019
- 2019
- [c20]Rachit Dubey, Pulkit Agrawal, Deepak Pathak, Alyosha A. Efros, Tom Griffiths:
Human-level but not human-like: Deep Reinforcement Learning in the dark. CogSci 2019: 3265 - [c19]Eliza Kosoy, Deepak Pathak, Pulkit Agrawal, Alison Gopnik:
Curiouser and Curiouser: Children's intrinsic exploration of mazes and its effects on reaching a goal. CogSci 2019: 3496 - [c18]Brian Cheung, Alexander Terekhov, Yubei Chen, Pulkit Agrawal, Bruno A. Olshausen:
Superposition of many models into one. NeurIPS 2019: 10867-10876 - [c17]Pulkit Agrawal, Rajat Arya, Aanchal Bindal, Sandeep Bhatia, Anupriya Gagneja, Joseph Godlewski, Yucheng Low, Timothy Muss, Mudit Manu Paliwal, Sethu Raman, Vishrut Shah, Bochao Shen, Laura Sugden, Kaiyu Zhao, Ming-Chuan Wu:
Data Platform for Machine Learning. SIGMOD Conference 2019: 1803-1816 - [i15]Brian Cheung, Alexander Terekhov, Yubei Chen, Pulkit Agrawal, Bruno A. Olshausen:
Superposition of many models into one. CoRR abs/1902.05522 (2019) - [i14]Richard Li, Allan Jabri, Trevor Darrell, Pulkit Agrawal:
Towards Practical Multi-Object Manipulation using Relational Reinforcement Learning. CoRR abs/1912.11032 (2019) - 2018
- [b1]Pulkit Agrawal:
Computational Sensorimotor Learning. University of California, Berkeley, USA, 2018 - [c16]Deepak Pathak, Yide Shentu, Dian Chen, Pulkit Agrawal, Trevor Darrell, Sergey Levine, Jitendra Malik:
Learning Instance Segmentation by Interaction. CVPR Workshops 2018: 2042-2045 - [c15]Deepak Pathak, Parsa Mahmoudieh, Guanghao Luo, Pulkit Agrawal, Dian Chen, Yide Shentu, Evan Shelhamer, Jitendra Malik, Alexei A. Efros
, Trevor Darrell:
Zero-Shot Visual Imitation. CVPR Workshops 2018: 2050-2053 - [c14]Rachit Dubey, Pulkit Agrawal, Deepak Pathak, Alyosha A. Efros, Thomas L. Griffiths:
Investigating Human Priors for Playing Video Games. ICLR (Workshop) 2018 - [c13]Deepak Pathak, Parsa Mahmoudieh, Guanghao Luo, Pulkit Agrawal, Dian Chen, Yide Shentu, Evan Shelhamer, Jitendra Malik, Alexei A. Efros, Trevor Darrell:
Zero-Shot Visual Imitation. ICLR 2018 - [c12]Rachit Dubey, Pulkit Agrawal, Deepak Pathak, Tom Griffiths, Alexei A. Efros:
Investigating Human Priors for Playing Video Games. ICML 2018: 1348-1356 - [i13]Rachit Dubey, Pulkit Agrawal, Deepak Pathak, Thomas L. Griffiths, Alexei A. Efros:
Investigating Human Priors for Playing Video Games. CoRR abs/1802.10217 (2018) - [i12]Deepak Pathak, Parsa Mahmoudieh, Guanghao Luo, Pulkit Agrawal, Dian Chen, Yide Shentu, Evan Shelhamer, Jitendra Malik, Alexei A. Efros, Trevor Darrell:
Zero-Shot Visual Imitation. CoRR abs/1804.08606 (2018) - [i11]Deepak Pathak, Yide Shentu, Dian Chen, Pulkit Agrawal, Trevor Darrell, Sergey Levine, Jitendra Malik:
Learning Instance Segmentation by Interaction. CoRR abs/1806.08354 (2018) - 2017
- [c11]Deepak Pathak, Pulkit Agrawal, Alexei A. Efros, Trevor Darrell:
Curiosity-Driven Exploration by Self-Supervised Prediction. CVPR Workshops 2017: 488-489 - [c10]Panna Felsen, Pulkit Agrawal, Jitendra Malik:
What will Happen Next? Forecasting Player Moves in Sports Videos. ICCV 2017: 3362-3371 - [c9]Misha Denil, Pulkit Agrawal, Tejas D. Kulkarni, Tom Erez, Peter W. Battaglia, Nando de Freitas:
Learning to Perform Physics Experiments via Deep Reinforcement Learning. ICLR (Poster) 2017 - [c8]Deepak Pathak, Pulkit Agrawal, Alexei A. Efros, Trevor Darrell:
Curiosity-driven Exploration by Self-supervised Prediction. ICML 2017: 2778-2787 - [c7]Ashvin Nair, Dian Chen, Pulkit Agrawal, Phillip Isola, Pieter Abbeel, Jitendra Malik, Sergey Levine:
Combining self-supervised learning and imitation for vision-based rope manipulation. ICRA 2017: 2146-2153 - [i10]Ashvin Nair, Dian Chen, Pulkit Agrawal, Phillip Isola, Pieter Abbeel, Jitendra Malik, Sergey Levine:
Combining Self-Supervised Learning and Imitation for Vision-Based Rope Manipulation. CoRR abs/1703.02018 (2017) - [i9]Deepak Pathak, Pulkit Agrawal, Alexei A. Efros, Trevor Darrell:
Curiosity-driven Exploration by Self-supervised Prediction. CoRR abs/1705.05363 (2017) - [i8]Amir R. Zamir, Tilman Wekel, Pulkit Agrawal, Colin Wei, Jitendra Malik, Silvio Savarese:
Generic 3D Representation via Pose Estimation and Matching. CoRR abs/1710.08247 (2017) - 2016
- [c6]João Carreira, Pulkit Agrawal, Katerina Fragkiadaki, Jitendra Malik:
Human Pose Estimation with Iterative Error Feedback. CVPR 2016: 4733-4742 - [c5]Amir R. Zamir, Tilman Wekel, Pulkit Agrawal, Colin Wei, Jitendra Malik, Silvio Savarese:
Generic 3D Representation via Pose Estimation and Matching. ECCV (3) 2016: 535-553 - [c4]Katerina Fragkiadaki, Pulkit Agrawal, Sergey Levine, Jitendra Malik:
Learning Visual Predictive Models of Physics for Playing Billiards. ICLR (Poster) 2016 - [i7]Pulkit Agrawal, Ashvin Nair, Pieter Abbeel, Jitendra Malik, Sergey Levine:
Learning to Poke by Poking: Experiential Learning of Intuitive Physics. CoRR abs/1606.07419 (2016) - [i6]Mi-Young Huh, Pulkit Agrawal, Alexei A. Efros:
What makes ImageNet good for transfer learning? CoRR abs/1608.08614 (2016) - [i5]Misha Denil, Pulkit Agrawal, Tejas D. Kulkarni, Tom Erez, Peter W. Battaglia, Nando de Freitas:
Learning to Perform Physics Experiments via Deep Reinforcement Learning. CoRR abs/1611.01843 (2016) - 2015
- [c3]Pulkit Agrawal, João Carreira, Jitendra Malik:
Learning to See by Moving. ICCV 2015: 37-45 - [i4]Pulkit Agrawal, João Carreira, Jitendra Malik:
Learning to See by Moving. CoRR abs/1505.01596 (2015) - [i3]João Carreira, Pulkit Agrawal, Katerina Fragkiadaki, Jitendra Malik:
Human Pose Estimation with Iterative Error Feedback. CoRR abs/1507.06550 (2015) - 2014
- [c2]Pulkit Agrawal, Ross B. Girshick, Jitendra Malik:
Analyzing the Performance of Multilayer Neural Networks for Object Recognition. ECCV (7) 2014: 329-344 - [i2]Pulkit Agrawal, Ross B. Girshick, Jitendra Malik:
Analyzing the Performance of Multilayer Neural Networks for Object Recognition. CoRR abs/1407.1610 (2014) - [i1]Pulkit Agrawal, Dustin Stansbury, Jitendra Malik, Jack L. Gallant:
Pixels to Voxels: Modeling Visual Representation in the Human Brain. CoRR abs/1407.5104 (2014) - 2011
- [c1]Gahgene Gweon, Pulkit Agrawal, Mikesh Udani, Bhiksha Raj, Carolyn P. Rosé:
The automatic assessment of knowledge integration processes in project teams. CSCL 2011
Coauthor Index
Alexei A. Efros
aka: Alyosha A. Efros
aka: Alyosha A. Efros
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