Tejas D. Kulkarni

Publication Activity (10 Years)

Years Active: 2011-2023
Publications (10 Years): 15

Top Topics

Reinforcement Learning

Top Venues

Publications

Antti Koskela, Tejas D. Kulkarni
Practical Differentially Private Hyperparameter Tuning with Subsampling. NeurIPS (2023)
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 (2019)
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)
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)
David Warde-Farley, Tom Van de Wiele, Tejas D. Kulkarni, Catalin Ionescu, Steven Hansen, Volodymyr Mnih
Unsupervised Control Through Non-Parametric Discriminative Rewards. CoRR (2018)
Ardavan Saeedi, Tejas D. Kulkarni, Vikash K. Mansinghka, Samuel J. Gershman
Variational Particle Approximations. J. Mach. Learn. Res. 18 (2017)
Michael Janner, Jiajun Wu, Tejas D. Kulkarni, Ilker Yildirim, Josh Tenenbaum
Self-Supervised Intrinsic Image Decomposition. NIPS (2017)
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)
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)
Michael Janner, Jiajun Wu, Tejas D. Kulkarni, Ilker Yildirim, Joshua B. Tenenbaum
Self-Supervised Intrinsic Image Decomposition. CoRR (2017)
Tejas D. Kulkarni, Ardavan Saeedi, Simanta Gautam, Samuel J. Gershman
Deep Successor Reinforcement Learning. CoRR (2016)
Tejas D. Kulkarni, Karthik Narasimhan, Ardavan Saeedi, Joshua B. Tenenbaum
Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation. CoRR (2016)
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 (2016)
William F. Whitney, Michael Chang, Tejas D. Kulkarni, Joshua B. Tenenbaum
Understanding Visual Concepts with Continuation Learning. CoRR (2016)
Tejas D. Kulkarni, Karthik Narasimhan, Ardavan Saeedi, Josh Tenenbaum
Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation. NIPS (2016)
Karthik Narasimhan, Tejas D. Kulkarni, Regina Barzilay
Language Understanding for Text-based Games Using Deep Reinforcement Learning. CoRR (2015)
Tejas D. Kulkarni, William F. Whitney, Pushmeet Kohli, Joshua B. Tenenbaum
Deep Convolutional Inverse Graphics Network. NIPS (2015)
Tejas D. Kulkarni, Will Whitney, Pushmeet Kohli, Joshua B. Tenenbaum
Deep Convolutional Inverse Graphics Network. CoRR (2015)
Tejas D. Kulkarni, Pushmeet Kohli, Joshua B. Tenenbaum, Vikash K. Mansinghka
Picture: A probabilistic programming language for scene perception. CVPR (2015)
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)
Karthik Narasimhan, Tejas D. Kulkarni, Regina Barzilay
Language Understanding for Text-based Games using Deep Reinforcement Learning. EMNLP (2015)
Tejas D. Kulkarni, Ardavan Saeedi, Samuel Gershman
Variational Particle Approximations. CoRR (2014)
Tejas D. Kulkarni, Vikash K. Mansinghka, Pushmeet Kohli, Joshua B. Tenenbaum
Inverse Graphics with Probabilistic CAD Models. CoRR (2014)
Vikash K. Mansinghka, Tejas D. Kulkarni, Yura N. Perov, Joshua B. Tenenbaum
Approximate Bayesian Image Interpretation using Generative Probabilistic Graphics Programs. NIPS (2013)
Vikash K. Mansinghka, Tejas D. Kulkarni, Yura N. Perov, Joshua B. Tenenbaum
Approximate Bayesian Image Interpretation using Generative Probabilistic Graphics Programs. CoRR (2013)
Sungahn Ko, KyungTae Kim, Tejas D. Kulkarni, Niklas Elmqvist
Applying mobile device soft keyboards to collaborative multitouch tabletop displays: design and evaluation. ITS (2011)