Tejas Kulkarni
Title
Cited by
Cited by
Year
Deep convolutional inverse graphics network
TD Kulkarni, WF Whitney, P Kohli, J Tenenbaum
Advances in neural information processing systems, 2539-2547, 2015
7082015
Hierarchical deep reinforcement learning: Integrating temporal abstraction and intrinsic motivation
TD Kulkarni, K Narasimhan, A Saeedi, J Tenenbaum
Advances in neural information processing systems, 3675-3683, 2016
6132016
Language understanding for text-based games using deep reinforcement learning
K Narasimhan, T Kulkarni, R Barzilay
arXiv preprint arXiv:1506.08941, 2015
2582015
Picture: a probabilistic programming language for scene perception
TD Kulkarni, P Kohli, JB Tenenbaum, VK Mansinghka
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2015
1612015
Synthesizing 3d shapes via modeling multi-view depth maps and silhouettes with deep generative networks
A Arsalan Soltani, H Huang, J Wu, TD Kulkarni, JB Tenenbaum
Proceedings of the IEEE conference on computer vision and pattern …, 2017
1222017
Deep successor reinforcement learning
TD Kulkarni, A Saeedi, S Gautam, SJ Gershman
arXiv preprint arXiv:1606.02396, 2016
1222016
Synthesizing programs for images using reinforced adversarial learning
Y Ganin, T Kulkarni, I Babuschkin, SM Eslami, O Vinyals
arXiv preprint arXiv:1804.01118, 2018
952018
Approximate bayesian image interpretation using generative probabilistic graphics programs
VK Mansinghka, TD Kulkarni, YN Perov, J Tenenbaum
Advances in Neural Information Processing Systems, 1520-1528, 2013
892013
Learning to perform physics experiments via deep reinforcement learning
M Denil, P Agrawal, TD Kulkarni, T Erez, P Battaglia, N De Freitas
arXiv preprint arXiv:1611.01843, 2016
562016
Use of association of an object detected in an image to obtain information to display to a user
TD Kulkarni, B Liu, AB Nandwani, JE Taseski, BJ Yule, D Kaleas, ...
US Patent App. 13/549,339, 2013
532013
Self-supervised intrinsic image decomposition
M Janner, J Wu, TD Kulkarni, I Yildirim, J Tenenbaum
Advances in Neural Information Processing Systems, 5936-5946, 2017
492017
Efficient and robust analysis-by-synthesis in vision: A computational framework, behavioral tests, and modeling neuronal representations
I Yildirim, TD Kulkarni, WA Freiwald, JB Tenenbaum
Annual conference of the cognitive science society 1 (2), 2015
422015
Unsupervised control through non-parametric discriminative rewards
D Warde-Farley, T Van de Wiele, T Kulkarni, C Ionescu, S Hansen, ...
arXiv preprint arXiv:1811.11359, 2018
402018
Understanding visual concepts with continuation learning
WF Whitney, M Chang, T Kulkarni, JB Tenenbaum
arXiv preprint arXiv:1602.06822, 2016
372016
Unsupervised learning of object keypoints for perception and control
TD Kulkarni, A Gupta, C Ionescu, S Borgeaud, M Reynolds, A Zisserman, ...
Advances in neural information processing systems, 10724-10734, 2019
292019
Inverse graphics with probabilistic cad models
TD Kulkarni, VK Mansinghka, P Kohli, JB Tenenbaum
arXiv preprint arXiv:1407.1339, 2014
192014
Deep Generative Vision as Approximate Bayesian Computation
TD Kulkarni, I Yildirim, P Kohli, WA Freiwald, JB Tenenbaum
Neural Information Processing Systems, 2014
182014
Efficient analysis-by-synthesis in vision: A computational framework, behavioral tests, and comparison with neural representations
I Yildirim, TD Kulkarni, WA Freiwald, JB Tenenbaum
Thirty-Seventh Annual Conference of the Cognitive Science Society 4, 2015
172015
Variational particle approximations
A Saeedi, TD Kulkarni, VK Mansinghka, SJ Gershman
The Journal of Machine Learning Research 18 (1), 2328-2356, 2017
162017
Applying mobile device soft keyboards to collaborative multitouch tabletop displays: design and evaluation
S Ko, KT Kim, T Kulkarni, N Elmqvist
Proceedings of the ACM international conference on Interactive tabletops and …, 2011
142011
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Articles 1–20