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Tejas D. Kulkarni
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2020 – today
- 2025
- [j2]Mounssif Krouka, Antti Koskela, Tejas D. Kulkarni:
Communication Efficient Differentially Private Federated Learning Using Second Order Information. Proc. Priv. Enhancing Technol. 2025(1): 584-612 (2025) - 2023
- [c13]Antti Koskela, Tejas D. Kulkarni:
Practical Differentially Private Hyperparameter Tuning with Subsampling. NeurIPS 2023
2010 – 2019
- 2019
- [c12]David Warde-Farley, Tom Van de Wiele, Tejas D. Kulkarni, Catalin Ionescu, Steven Hansen, Volodymyr Mnih:
Unsupervised Control Through Non-Parametric Discriminative Rewards. ICLR (Poster) 2019 - [c11]Tejas D. Kulkarni, Ankush Gupta, Catalin Ionescu, Sebastian Borgeaud, Malcolm Reynolds, Andrew Zisserman, Volodymyr Mnih:
Unsupervised Learning of Object Keypoints for Perception and Control. NeurIPS 2019: 10723-10733 - [i12]Tejas D. Kulkarni, Ankush Gupta, Catalin Ionescu, Sebastian Borgeaud, Malcolm Reynolds, Andrew Zisserman, Volodymyr Mnih:
Unsupervised Learning of Object Keypoints for Perception and Control. CoRR abs/1906.11883 (2019) - 2018
- [i11]David Warde-Farley, Tom Van de Wiele, Tejas D. Kulkarni, Catalin Ionescu, Steven Hansen, Volodymyr Mnih:
Unsupervised Control Through Non-Parametric Discriminative Rewards. CoRR abs/1811.11359 (2018) - 2017
- [j1]Ardavan Saeedi, Tejas D. Kulkarni, Vikash K. Mansinghka, Samuel J. Gershman:
Variational Particle Approximations. J. Mach. Learn. Res. 18: 69:1-69:29 (2017) - [c10]Amir Arsalan Soltani, Haibin Huang, Jiajun Wu, Tejas D. Kulkarni, Joshua B. Tenenbaum:
Synthesizing 3D Shapes via Modeling Multi-view Depth Maps and Silhouettes with Deep Generative Networks. CVPR 2017: 2511-2519 - [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]Michael Janner, Jiajun Wu, Tejas D. Kulkarni, Ilker Yildirim, Josh Tenenbaum:
Self-Supervised Intrinsic Image Decomposition. NIPS 2017: 5936-5946 - [i10]Michael Janner, Jiajun Wu, Tejas D. Kulkarni, Ilker Yildirim, Joshua B. Tenenbaum:
Self-Supervised Intrinsic Image Decomposition. CoRR abs/1711.03678 (2017) - 2016
- [c7]Tejas D. Kulkarni, Karthik Narasimhan, Ardavan Saeedi, Josh Tenenbaum:
Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation. NIPS 2016: 3675-3683 - [i9]William F. Whitney, Michael Chang, Tejas D. Kulkarni, Joshua B. Tenenbaum:
Understanding Visual Concepts with Continuation Learning. CoRR abs/1602.06822 (2016) - [i8]Tejas D. Kulkarni, Karthik Narasimhan, Ardavan Saeedi, Joshua B. Tenenbaum:
Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation. CoRR abs/1604.06057 (2016) - [i7]Tejas D. Kulkarni, Ardavan Saeedi, Simanta Gautam, Samuel J. Gershman:
Deep Successor Reinforcement Learning. CoRR abs/1606.02396 (2016) - [i6]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
- [c6]Ilker Yildirim, Tejas D. Kulkarni, Winrich Freiwald, Joshua B. Tenenbaum:
Efficient analysis-by-synthesis in vision: A computational framework, behavioral tests, and modeling neuronal representations. CogSci 2015 - [c5]Tejas D. Kulkarni, Pushmeet Kohli, Joshua B. Tenenbaum, Vikash Mansinghka:
Picture: A probabilistic programming language for scene perception. CVPR 2015: 4390-4399 - [c4]Karthik Narasimhan, Tejas D. Kulkarni, Regina Barzilay:
Language Understanding for Text-based Games using Deep Reinforcement Learning. EMNLP 2015: 1-11 - [c3]Tejas D. Kulkarni, William F. Whitney, Pushmeet Kohli, Joshua B. Tenenbaum:
Deep Convolutional Inverse Graphics Network. NIPS 2015: 2539-2547 - [i5]Tejas D. Kulkarni, Will Whitney, Pushmeet Kohli, Joshua B. Tenenbaum:
Deep Convolutional Inverse Graphics Network. CoRR abs/1503.03167 (2015) - [i4]Karthik Narasimhan, Tejas D. Kulkarni, Regina Barzilay:
Language Understanding for Text-based Games Using Deep Reinforcement Learning. CoRR abs/1506.08941 (2015) - 2014
- [i3]Tejas D. Kulkarni, Ardavan Saeedi, Samuel Gershman:
Variational Particle Approximations. CoRR abs/1402.5715 (2014) - [i2]Tejas D. Kulkarni, Vikash K. Mansinghka, Pushmeet Kohli, Joshua B. Tenenbaum:
Inverse Graphics with Probabilistic CAD Models. CoRR abs/1407.1339 (2014) - 2013
- [c2]Vikash K. Mansinghka, Tejas D. Kulkarni, Yura N. Perov, Joshua B. Tenenbaum:
Approximate Bayesian Image Interpretation using Generative Probabilistic Graphics Programs. NIPS 2013: 1520-1528 - [i1]Vikash K. Mansinghka, Tejas D. Kulkarni, Yura N. Perov, Joshua B. Tenenbaum:
Approximate Bayesian Image Interpretation using Generative Probabilistic Graphics Programs. CoRR abs/1307.0060 (2013) - 2011
- [c1]Sungahn Ko, KyungTae Kim, Tejas D. Kulkarni, Niklas Elmqvist
:
Applying mobile device soft keyboards to collaborative multitouch tabletop displays: design and evaluation. ITS 2011: 130-139
Coauthor Index
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