Tejas D. Kulkarni

29 papers A* 5B 2Journal 16Unranked 6

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Communication Efficient Differentially Private Federated Learning Using Second Order Information. Proc. Priv. Enhancing Technol. Mounssif Krouka, Antti Koskela, Tejas D. Kulkarni
2025	J	`jnl`	Differential Privacy Analysis of Decentralized Gossip Averaging under Varying Threat Models. CoRR Antti Koskela, Tejas D. Kulkarni
2025	J	`jnl`	Differentially Private In-Context Learning with Nearest Neighbor Search. CoRR Antti Koskela, Tejas D. Kulkarni, Laith Y. Zumot
2023	A*	`conf`	Practical Differentially Private Hyperparameter Tuning with Subsampling. NeurIPS Antti Koskela, Tejas D. Kulkarni
2019	—	`conf`	Unsupervised Control Through Non-Parametric Discriminative Rewards. ICLR (Poster) David Warde-Farley, Tom Van de Wiele, Tejas D. Kulkarni, Catalin Ionescu, Steven Hansen, Volodymyr Mnih
2019	A*	`conf`	Unsupervised Learning of Object Keypoints for Perception and Control. NeurIPS Tejas D. Kulkarni, Ankush Gupta, Catalin Ionescu, Sebastian Borgeaud, Malcolm Reynolds, Andrew Zisserman, Volodymyr Mnih
2019	J	`jnl`	Unsupervised Learning of Object Keypoints for Perception and Control. CoRR Tejas D. Kulkarni, Ankush Gupta, Catalin Ionescu, Sebastian Borgeaud, Malcolm Reynolds, Andrew Zisserman, Volodymyr Mnih
2018	J	`jnl`	Unsupervised Control Through Non-Parametric Discriminative Rewards. CoRR David Warde-Farley, Tom Van de Wiele, Tejas D. Kulkarni, Catalin Ionescu, Steven Hansen, Volodymyr Mnih
2017	—	`conf`	Learning to Perform Physics Experiments via Deep Reinforcement Learning. ICLR (Poster) Misha Denil, Pulkit Agrawal, Tejas D. Kulkarni, Tom Erez, Peter W. Battaglia, Nando de Freitas
2017	—	`conf`	Self-Supervised Intrinsic Image Decomposition. NIPS Michael Janner, Jiajun Wu, Tejas D. Kulkarni, Ilker Yildirim, Josh Tenenbaum
2017	J	`jnl`	Self-Supervised Intrinsic Image Decomposition. CoRR Michael Janner, Jiajun Wu, Tejas D. Kulkarni, Ilker Yildirim, Joshua B. Tenenbaum
2017	A*	`conf`	Synthesizing 3D Shapes via Modeling Multi-view Depth Maps and Silhouettes with Deep Generative Networks. CVPR Amir Arsalan Soltani, Haibin Huang, Jiajun Wu, Tejas D. Kulkarni, Joshua B. Tenenbaum
2017	J	`jnl`	Variational Particle Approximations. J. Mach. Learn. Res. Ardavan Saeedi, Tejas D. Kulkarni, Vikash K. Mansinghka, Samuel J. Gershman
2016	J	`jnl`	Deep Successor Reinforcement Learning. CoRR Tejas D. Kulkarni, Ardavan Saeedi, Simanta Gautam, Samuel J. Gershman
2016	—	`conf`	Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation. NIPS Tejas D. Kulkarni, Karthik Narasimhan, Ardavan Saeedi, Josh Tenenbaum
2016	J	`jnl`	Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation. CoRR Tejas D. Kulkarni, Karthik Narasimhan, Ardavan Saeedi, Joshua B. Tenenbaum
2016	J	`jnl`	Learning to Perform Physics Experiments via Deep Reinforcement Learning. CoRR Misha Denil, Pulkit Agrawal, Tejas D. Kulkarni, Tom Erez, Peter W. Battaglia, Nando de Freitas
2016	J	`jnl`	Understanding Visual Concepts with Continuation Learning. CoRR William F. Whitney, Michael Chang, Tejas D. Kulkarni, Joshua B. Tenenbaum
2015	—	`conf`	Deep Convolutional Inverse Graphics Network. NIPS Tejas D. Kulkarni, William F. Whitney, Pushmeet Kohli, Joshua B. Tenenbaum
2015	J	`jnl`	Deep Convolutional Inverse Graphics Network. CoRR Tejas D. Kulkarni, Will Whitney, Pushmeet Kohli, Joshua B. Tenenbaum
2015	B	`conf`	Efficient analysis-by-synthesis in vision: A computational framework, behavioral tests, and modeling neuronal representations. CogSci Ilker Yildirim, Tejas D. Kulkarni, Winrich Freiwald, Joshua B. Tenenbaum
2015	J	`jnl`	Language Understanding for Text-based Games Using Deep Reinforcement Learning. CoRR Karthik Narasimhan, Tejas D. Kulkarni, Regina Barzilay
2015	A*	`conf`	Language Understanding for Text-based Games using Deep Reinforcement Learning. EMNLP Karthik Narasimhan, Tejas D. Kulkarni, Regina Barzilay
2015	A*	`conf`	Picture: A probabilistic programming language for scene perception. CVPR Tejas D. Kulkarni, Pushmeet Kohli, Joshua B. Tenenbaum, Vikash Mansinghka
2014	J	`jnl`	Inverse Graphics with Probabilistic CAD Models. CoRR Tejas D. Kulkarni, Vikash K. Mansinghka, Pushmeet Kohli, Joshua B. Tenenbaum
2014	J	`jnl`	Variational Particle Approximations. CoRR Tejas D. Kulkarni, Ardavan Saeedi, Samuel Gershman
2013	—	`conf`	Approximate Bayesian Image Interpretation using Generative Probabilistic Graphics Programs. NIPS Vikash K. Mansinghka, Tejas D. Kulkarni, Yura N. Perov, Joshua B. Tenenbaum
2013	J	`jnl`	Approximate Bayesian Image Interpretation using Generative Probabilistic Graphics Programs. CoRR Vikash K. Mansinghka, Tejas D. Kulkarni, Yura N. Perov, Joshua B. Tenenbaum
2011	B	`conf`	Applying mobile device soft keyboards to collaborative multitouch tabletop displays: design and evaluation. ITS Sungahn Ko, Kyungtae Kim, Tejas D. Kulkarni, Niklas Elmqvist