Josh Tenenbaum
Impact in
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- Multimodal Machine Learning Applications
- Advanced Image and Video Retrieval Techniques
- Human Pose and Action Recognition
- Advanced Vision and Imaging
- Generative Adversarial Networks and Image Synthesis
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- Child and Animal Learning Development
Papers in
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- Machine Learning and Algorithms 6
- Reinforcement Learning in Robotics 6
- Domain Adaptation and Few-Shot Learning 6
- Gaussian Processes and Bayesian Inference 6
- Co-authors
- Ruslan SalakhutdinovAntonio TorralbaRebecca SaxeSusan CareyBrenden M. LakeKelsey R. AllenJiajun WuTomer Ullman
- Journals
- Cognitive Science (20 papers)Journal of Vision (3 papers)Optics Communications (3 papers)Journal of Applied Physics (2 papers)Developmental Science (2 papers)
- Partner nations
- United StatesUnited KingdomCanada
In The Last Decade
Josh Tenenbaum
71 papers receiving 1.5k citations
Peers
Comparison fields: 5 of 130
- Computer Vision and Pattern Recognition 604
- Developmental and Educational Psychology 331
- Computer Graphics and Computer-Aided Design 85
- Artificial Intelligence 593
- General Decision Sciences 29
Countries citing papers authored by Josh Tenenbaum
This map shows the geographic impact of Josh Tenenbaum's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Josh Tenenbaum with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Josh Tenenbaum more than expected).
Fields of papers citing papers by Josh Tenenbaum
This network shows the impact of papers produced by Josh Tenenbaum. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Josh Tenenbaum. The network helps show where Josh Tenenbaum may publish in the future.
Co-authors
The 25 scholars most cited alongside Josh Tenenbaum, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Learning Signal-Agnostic Implicit Manifolds | 2021 | 1 |
| 2 | Adventures in Flatland: Perceiving Social Interactions Under Physical Dynamics. | 2020 | 6 |
| 3 | Leveraging Unstructured Statistical Knowledge in a Probabilistic Language of Thought. | 2020 | 1 |
| 4 | Few-Shot Bayesian Imitation Learning with Logic over Programs. | 2019 | 4 |
| 5 | Draping an Elephant: Uncovering Children's Reasoning About Cloth-Covered Objects. | 2019 | 1 |
| 6 | Discovering a symbolic planning language from continuous experience. | 2019 | 1 |
| 7 | Rapid Trial-and-Error Learning in Physical Problem Solving. | 2019 | 1 |
| 8 | 2018 | 4 | |
| 9 | End-to-End Differentiable Physics for Learning and Control | 2018 | 129 |
| 10 | Meta-Learning for Semi-Supervised Few-Shot Classification | 2018 | 73 |
| 11 | The Cognitive Mechanisms of Contractualist Moral Decision-Making. | 2018 | 2 |
| 12 | Constructing Social Preferences From Anticipated Judgments: When Impartial Inequity is Fair and Why? | 2017 | 10 |
| 13 | Causal and compositional generative models in online perception. | 2017 | 3 |
| 14 | Shape and material from sound | 2017 | 12 |
| 15 | Learning to See Physics via Visual De-animation | 2017 | 42 |
| 16 | Coalescing the Vapors of Human Experience into a Viable and Meaningful Comprehension. | 2016 | 2 |
| 17 | Understanding "almost": Empirical and computational studies of near misses. | 2016 | 3 |
| 18 | Cognitive Decision Theory: Developing Models of Real-World Decision Behavior | 2007 | 3 |
| 19 | Learning Inductive Constraints: The Acquisition of Verb Argument Constructions | 2007 | 3 |
| 20 | Probabilistic models of cognition. Special Issue. | 2006 | 6 |
About Josh Tenenbaum
Josh Tenenbaum is a scholar working on General Decision Sciences, Artificial Intelligence, Developmental and Educational Psychology, Computer Vision and Pattern Recognition and Computer Science Applications, having authored 76 papers that have together received 1.6k indexed citations. Recurring topics across this work include Child and Animal Learning Development (13 papers), Laser Design and Applications (7 papers), Spectroscopy and Laser Applications (7 papers), Advanced Vision and Imaging (7 papers), Machine Learning and Algorithms (6 papers), Reinforcement Learning in Robotics (6 papers), Domain Adaptation and Few-Shot Learning (6 papers) and Gaussian Processes and Bayesian Inference (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (604 citations), Developmental and Educational Psychology (331 citations), Computer Graphics and Computer-Aided Design (85 citations), Artificial Intelligence (593 citations) and General Decision Sciences (29 citations). Josh Tenenbaum has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Ruslan Salakhutdinov, Antonio Torralba, Rebecca Saxe, Susan Carey, Brenden M. Lake, Kelsey R. Allen, Jiajun Wu, Tomer Ullman, Kevin A. Smith and Bill Freeman. Their work appears in journals such as Cognitive Science, Journal of Vision, Optics Communications, Journal of Applied Physics and Developmental Science.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.