Publications

    Tejas D Kulkarni

  • Tejas D Kulkarni, Karthik Narasimhan, Ardavan Saeedi, Josh Tenenbaum:
    Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation (web) (bibtex)
    Advances in Neural Information Processing Systems (NIPS)
    #reinforcement learning, #hierarchical modeling, #deep learning
    @article{TejasDKulkarni:2016:847fe,
    author = {Tejas D Kulkarni and Karthik Narasimhan and Ardavan Saeedi and Josh Tenenbaum},
    journal = {Advances in Neural Information Processing Systems (NIPS)},
    title = {Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation},
    year = {2016},
    keywords = {reinforcement learning, hierarchical modeling, deep learning},
    doi = {},
    url = {http://papers.nips.cc/paper/6232-hierarchical-deep-reinforcement-learning-integrating-temporal-abstraction-and-intrinsic-motivation}
    }
  • Tejas D Kulkarni, William F Whitney, Pushmeet Kohli, Josh Tenenbaum:
    Deep Convolutional Inverse Graphics Network (web) (bibtex)
    Advances in Neural Information Processing Systems (NIPS)
    #inverse vision, #deep learning, #disentangled representation,
    @article{TejasDKulkarni:2015:19456,
    author = {Tejas D Kulkarni and William F Whitney and Pushmeet Kohli and Josh Tenenbaum},
    journal = {Advances in Neural Information Processing Systems (NIPS)},
    title = {Deep Convolutional Inverse Graphics Network},
    year = {2015},
    keywords = {inverse vision, deep learning, disentangled representation,},
    doi = {},
    url = {http://papers.nips.cc/paper/5851-deep-convolutional-inverse-graphics-network}
    }
  • Tejas D Kulkarni, Pushmeet Kohli, Joshua B Tenenbaum, Vikash Mansinghka:
    Picture : A Probabilistic Programming Language for Scene Perception (pdf) (doi) (bibtex)
    Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition
    #analysis-by-synthesis, #inference, #deep learning, #inverse vision, #3d vision, #probabilistic programming
    @article{TejasDKulkarni:2015:cf27d,
    author = {Tejas D Kulkarni and Pushmeet Kohli and Joshua B Tenenbaum and Vikash Mansinghka},
    journal = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
    title = {Picture : A Probabilistic Programming Language for Scene Perception},
    year = {2015},
    keywords = {analysis-by-synthesis, inference, deep learning, inverse vision, 3d vision, probabilistic programming},
    doi = {10.1109/CVPR.2015.7299068},
    url = {http://openaccess.thecvf.com/content_cvpr_2015/papers/Kulkarni_Picture_A_Probabilistic_2015_CVPR_paper.pdf}
    }
  • 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 (web) (doi) (bibtex)
    IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
    #2d to 3d, #3d vision, #3d generation, #3d reconstruction, #inverse vision, #scene understanding, #deep learning
    @article{AmirArsalanSoltani:2017:4a1d2,
    author = {Amir Arsalan Soltani and Haibin Huang and Jiajun Wu and Tejas D Kulkarni and Joshua B Tenenbaum},
    journal = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
    title = {Synthesizing 3D Shapes via Modeling Multi-View Depth Maps and Silhouettes with Deep Generative },
    year = {2017},
    keywords = {2d to 3d, 3d vision, 3d generation, 3d reconstruction, inverse vision, scene understanding, deep learning},
    doi = {10.1109/CVPR.2017.269},
    url = {https://github.com/Amir-Arsalan/Synthesize3DviaDepthOrSil}
    }

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