Publications

Joshua B Tenenbaum

• Kevin A Smith, Filipe de A B Peres, Edward Vul, Joshua B Tenenbaum:
  Thinking inside the box: Motion prediction in contained spaces uses simulation (pdf) (bibtex)
  Cognitive Science Society
  #intuitive physics, #simulation, #topology, #containers
  @article{KevinASmith:2017:2a5ea,
  author = {Kevin A Smith and Filipe de A B Peres and Edward Vul and Joshua B Tenenbaum},
  journal = {Cognitive Science Society},
  title = {Thinking inside the box: Motion prediction in contained spaces uses simulation},
  year = {2017},
  keywords = {intuitive physics, simulation, topology, containers},
  doi = {},
  url = {http://scripts.mit.edu/~k2smith/publications/Smith_CogSci_Topology.pdf}
  }
  
• Tobias Gerstenberg, Matthew F Peterson, Noah D Goodman, David A Lagnado, Joshua B Tenenbaum:
  Eye-Tracking Causality (web) (doi) (bibtex)
  Psychological Science
  #causality, #counterfactuals, #mental simulation, #intuitive physics, #eye tracking, #open data, #open materials
  @article{TobiasGerstenberg:2017:9fd98,
  author = {Tobias Gerstenberg and Matthew F Peterson and Noah D Goodman and David A Lagnado and Joshua B Tenenbaum},
  journal = {Psychological Science},
  title = { Eye-Tracking Causality},
  year = {2017},
  keywords = {causality, counterfactuals, mental simulation, intuitive physics, eye tracking, open data, open materials},
  doi = {10.1177/0956797617713053},
  url = {http://journals.sagepub.com/doi/10.1177/0956797617713053}
  }
  
• Shari Liu, Tomer D Ullman, Joshua B Tenenbaum, Elizabeth S Spelke:
  Ten-month-old infants infer the value of goals from the costs of actions (web) (doi) (bibtex)
  Science
  #intuitive psychology, #inverse planning, #action-value prediction
  @article{ShariLiu:2017:c07d1,
  author = {Shari Liu and Tomer D Ullman and Joshua B Tenenbaum and Elizabeth S Spelke},
  journal = {Science},
  title = {Ten-month-old infants infer the value of goals from the costs of actions},
  year = {2017},
  keywords = {intuitive psychology, inverse planning, action-value prediction},
  doi = {10.1126/science.aag2132 },
  url = {http://science.sciencemag.org/content/358/6366/1038}
  }
  
• Brenden M Lake, Tomer D Ullman, Joshua B Tenenbaum, Samuel J Gershman:
  Building Machines That Learn and Think Like People (web) (doi) (bibtex)
  Behavioral and Brain Sciences
  #artificial intelligence, #intuitive theories, #intuitive physics, #intuitive psychology, #compositionality, #learning to learn
  @article{BrendenMLake:2017:59b19,
  author = {Brenden M Lake and Tomer D Ullman and Joshua B Tenenbaum and Samuel J Gershman},
  journal = {Behavioral and Brain Sciences},
  title = {Building Machines That Learn and Think Like People},
  year = {2017},
  keywords = {artificial intelligence, intuitive theories, intuitive physics, intuitive psychology, compositionality, learning to learn},
  doi = {10.1017/S0140525X16001837},
  url = {https://www.cambridge.org/core/journals/behavioral-and-brain-sciences/article/building-machines-that-learn-and-think-like-people/A9535B1D745A0377E16C590E14B94993}
  }
  
• Brenden M Lake, Ruslan Salakhutdinov, Joshua B Tenenbaum:
  Human-Level Concept Learning Through Probabilistic Program Induction (web) (doi) (bibtex)
  Science
  #concept learning, #program induction, #motor skills, #artificial intelligence, #learning to learn, #bayesian, #one-shot learning
  @article{BrendenMLake:2015:e5493,
  author = {Brenden M Lake and Ruslan Salakhutdinov and Joshua B Tenenbaum},
  journal = {Science},
  title = {Human-Level Concept Learning Through Probabilistic Program Induction},
  year = {2015},
  keywords = {concept learning, program induction, motor skills, artificial intelligence, learning to learn, bayesian, one-shot learning},
  doi = {10.1126/science.aab3050},
  url = {science.sciencemag.org/content/350/6266/1332.short}
  }
  
• 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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