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ORCIDKumar Krishna Agrawal
Person information
- affiliation: Google Brain, Mountain View, CA, USA
- affiliation: Indian Institute of Technology Kharagpur, India
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2020 – today
- 2024
[c12]Ian Berlot-Attwell, Kumar Krishna Agrawal, Annabelle Michael Carrell, Yash Sharma, Naomi Saphra:
Attribute Diversity Determines the Systematicity Gap in VQA. EMNLP 2024: 9576-9611- 2023
- [i10]Ian Berlot-Attwell, A. Michael Carrell, Kumar Krishna Agrawal, Yash Sharma, Naomi Saphra:
Attribute Diversity Determines the Systematicity Gap in VQA. CoRR abs/2311.08695 (2023) - [i9]Kumar Krishna Agrawal, Arna Ghosh, Adam Oberman, Blake A. Richards:
Addressing Sample Inefficiency in Multi-View Representation Learning. CoRR abs/2312.10725 (2023) - 2022
- [c11]Wenshuo Guo, Kumar Krishna Agrawal, Aditya Grover, Vidya K. Muthukumar, Ashwin Pananjady:
Learning from an Exploring Demonstrator: Optimal Reward Estimation for Bandits. AISTATS 2022: 6357-6386 - [c10]Gur-Eyal Sela, Ionel Gog, Justin Wong, Kumar Krishna Agrawal, Xiangxi Mo, Sukrit Kalra, Peter Schafhalter, Eric Leong, Xin Wang, Bharathan Balaji, Joseph Gonzalez
, Ion Stoica:
Context-Aware Streaming Perception in Dynamic Environments. ECCV (38) 2022: 621-638 - [c9]Kumar Krishna Agrawal, Arnab Kumar Mondal, Arna Ghosh, Blake A. Richards:
$\alpha$-ReQ : Assessing Representation Quality in Self-Supervised Learning by measuring eigenspectrum decay. NeurIPS 2022 - [i8]Arna Ghosh, Arnab Kumar Mondal, Kumar Krishna Agrawal, Blake A. Richards:
Investigating Power laws in Deep Representation Learning. CoRR abs/2202.05808 (2022) - [i7]Gur-Eyal Sela, Ionel Gog, Justin Wong, Kumar Krishna Agrawal, Xiangxi Mo, Sukrit Kalra, Peter Schafhalter, Eric Leong, Xin Wang, Bharathan Balaji, Joseph Gonzalez, Ion Stoica:
Context-Aware Streaming Perception in Dynamic Environments. CoRR abs/2208.07479 (2022) - 2021
- [i6]Wenshuo Guo, Kumar Krishna Agrawal, Aditya Grover, Vidya Muthukumar, Ashwin Pananjady:
Learning from an Exploring Demonstrator: Optimal Reward Estimation for Bandits. CoRR abs/2106.14866 (2021) - 2020
- [c8]Todd W. Neller, Stephen Keeley, Michael Guerzhoy, Wolfgang Hönig, Jiaoyang Li, Sven Koenig, Ameet Soni, Krista Thomason, Lisa Zhang, Bibin Sebastian, Cinjon Resnick, Avital Oliver, Surya Bhupatiraju, Kumar Krishna Agrawal, James Allingham, Sejong Yoon, Jonathan Chen, Tom Larsen, Marion Neumann, Narges Norouzi, Ryan Hausen, Matthew Evett:
Model AI Assignments 2020. AAAI 2020: 13509-13511
2010 – 2019
- 2019
- [c7]Todd W. Neller, Raja Sooriamurthi, Michael Guerzhoy, Lisa Zhang, Paul Talaga, Christopher Archibald, Adam Summerville, Joseph C. Osborn, Cinjon Resnick, Avital Oliver, Surya Bhupatiraju, Kumar Krishna Agrawal, Nate Derbinsky, Elena Strange, Marion Neumann, Jonathan Chen, Zac Christensen, Michael Wollowski, Oscar Youngquist:
Model AI Assignments 2019. AAAI 2019: 9751-9753 - [c6]Jesse H. Engel, Kumar Krishna Agrawal, Shuo Chen, Ishaan Gulrajani, Chris Donahue, Adam Roberts:
GANSynth: Adversarial Neural Audio Synthesis. ICLR (Poster) 2019 - [c5]Ilya Kostrikov, Kumar Krishna Agrawal, Debidatta Dwibedi, Sergey Levine, Jonathan Tompson:
Discriminator-Actor-Critic: Addressing Sample Inefficiency and Reward Bias in Adversarial Imitation Learning. ICLR (Poster) 2019 - [c4]Dustin Tran, Keyon Vafa, Kumar Krishna Agrawal, Laurent Dinh, Ben Poole:
Discrete Flows: Invertible Generative Models of Discrete Data. DGS@ICLR 2019 - [c3]Dustin Tran, Keyon Vafa, Kumar Krishna Agrawal, Laurent Dinh, Ben Poole:
Discrete Flows: Invertible Generative Models of Discrete Data. NeurIPS 2019: 14692-14701 - [i5]Jesse H. Engel, Kumar Krishna Agrawal, Shuo Chen, Ishaan Gulrajani, Chris Donahue, Adam Roberts:
GANSynth: Adversarial Neural Audio Synthesis. CoRR abs/1902.08710 (2019) - [i4]Dustin Tran, Keyon Vafa, Kumar Krishna Agrawal, Laurent Dinh, Ben Poole:
Discrete Flows: Invertible Generative Models of Discrete Data. CoRR abs/1905.10347 (2019) - 2018
- [i3]Surya Bhupatiraju, Kumar Krishna Agrawal, Rishabh Singh:
Towards Mixed Optimization for Reinforcement Learning with Program Synthesis. CoRR abs/1807.00403 (2018) - [i2]Ilya Kostrikov, Kumar Krishna Agrawal, Sergey Levine, Jonathan Tompson:
Addressing Sample Inefficiency and Reward Bias in Inverse Reinforcement Learning. CoRR abs/1809.02925 (2018) - 2017
- [c2]Arnav Kumar Jain, Abhinav Agarwalla, Kumar Krishna Agrawal, Pabitra Mitra:
Recurrent Memory Addressing for Describing Videos. CVPR Workshops 2017: 2200-2207 - [c1]Anmol Gulati, Kumar Krishna Agrawal:
Playing with Embeddings : Evaluating embeddings for Robot Language Learning through MUD Games. RepEval@EMNLP 2017: 27-30 - 2016
- [i1]Kumar Krishna Agrawal, Arnav Kumar Jain, Abhinav Agarwalla, Pabitra Mitra:
Recurrent Memory Addressing for describing videos. CoRR abs/1611.06492 (2016)
Coauthor Index
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