← Authors

Josh Tenenbaum

67 papers · 2013–2023 · 4 conferences · across top CS/AI conferences

Achievements

πŸ—ΊοΈ Taxonomy Completionist (98) 🌍 Conference Polyglot (4) 🌈 Renaissance Researcher (10) πŸŒ‰ Interdisciplinary Bridge 🐝 Cross-Pollinator (13) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird πŸƒ Academic Marathon (10) 🌟 Keyword Trendsetter Combo (8) 🏠 Conference Loyalist (64) 🀝 Dynamic Duo (17) 🌱 Topic Pioneer πŸ”¬ Deep Specialist (15) 🧬 Topic Evolution πŸ† Keyword Champion (3) πŸ’Ž Century Club (67) πŸ—ƒοΈ Keyword Collector (350) πŸ”₯ Unstoppable (9) πŸ“ˆ Trend Setter ❓ The Questioner (2) ⚑ Prolific Year (11)

Conferences

NIPS (64) AAAI (1) EMNLP (1) ICML (1)

Top co-authors

Jiajun Wu (17) Bill Freeman (12) Chuang Gan (10) Yilun Du (9) Antonio Torralba (7) Jiayuan Mao (7) Kevin Ellis (7) Armando Solar-Lezama (7) Brenden M Lake (4) Tejas D Kulkarni (4)

Research topics

Computer Vision (1)

Keywords

generative model (8) scene understanding (7) bayesian inference (7) program synthesis (7) visual reasoning (5) 3d reconstruction (5) few-shot learning (4) representation learning (4) 3d vision (4) graph neural network (4) neural network (4) 3d scene understanding (3) inductive bia (3) physical reasoning (3) program induction (3) visual concept learning (3) convolutional neural network (3) unsupervised learning (3) reinforcement learning (3) concept learning (3)

Papers

Learning Universal Policies via Text-Guided Video Generation NIPS 2023
What Planning Problems Can A Relational Neural Network Solve? NIPS 2023
Human spatiotemporal pattern learning as probabilistic program synthesis NIPS 2023
Physion++: Evaluating Physical Scene Understanding that Requires Online Inference of Different Physical Properties NIPS 2023
DiffuseBot: Breeding Soft Robots With Physics-Augmented Generative Diffusion Models NIPS 2023
3D-IntPhys: Towards More Generalized 3D-grounded Visual Intuitive Physics under Challenging Scenes NIPS 2023
What’s Left? Concept Grounding with Logic-Enhanced Foundation Models NIPS 2023
Compositional Foundation Models for Hierarchical Planning NIPS 2023
Inferring the Future by Imagining the Past NIPS 2023
Diffusion with Forward Models: Solving Stochastic Inverse Problems Without Direct Supervision NIPS 2023
Revisiting the Roles of β€œText” in Text Games EMNLP 2022
PDSketch: Integrated Domain Programming, Learning, and Planning NIPS 2022
When to Make Exceptions: Exploring Language Models as Accounts of Human Moral Judgment NIPS 2022
Learning Physical Dynamics with Subequivariant Graph Neural Networks NIPS 2022
Drawing out of Distribution with Neuro-Symbolic Generative Models NIPS 2022
HandMeThat: Human-Robot Communication in Physical and Social Environments NIPS 2022
3D Concept Grounding on Neural Fields NIPS 2022
Communicating Natural Programs to Humans and Machines NIPS 2022
Learning Neural Acoustic Fields NIPS 2022
A Bayesian-Symbolic Approach to Reasoning and Learning in Intuitive Physics NIPS 2021
Improving Coherence and Consistency in Neural Sequence Models with Dual-System, Neuro-Symbolic Reasoning NIPS 2021
Learning to Compose Visual Relations NIPS 2021
Dynamic Visual Reasoning by Learning Differentiable Physics Models from Video and Language NIPS 2021
Light Field Networks: Neural Scene Representations with Single-Evaluation Rendering NIPS 2021
PTR: A Benchmark for Part-based Conceptual, Relational, and Physical Reasoning NIPS 2021
Noether Networks: meta-learning useful conserved quantities NIPS 2021
Unsupervised Learning of Compositional Energy Concepts NIPS 2021
3DP3: 3D Scene Perception via Probabilistic Programming NIPS 2021
Learning Signal-Agnostic Manifolds of Neural Fields NIPS 2021
Grammar-Based Grounded Lexicon Learning NIPS 2021
Program Synthesis with Pragmatic Communication NIPS 2020
Learning abstract structure for drawing by efficient motor program induction NIPS 2020
Learning Physical Graph Representations from Visual Scenes NIPS 2020
Multi-Plane Program Induction with 3D Box Priors NIPS 2020
Learning Compositional Rules via Neural Program Synthesis NIPS 2020
Online Bayesian Goal Inference for Boundedly Rational Planning Agents NIPS 2020
Few-Shot Bayesian Imitation Learning with Logical Program Policies AAAI 2020
Modeling Expectation Violation in Intuitive Physics with Coarse Probabilistic Object Representations NIPS 2019
Visual Concept-Metaconcept Learning NIPS 2019
ObjectNet: A large-scale bias-controlled dataset for pushing the limits of object recognition models NIPS 2019
Finding Friend and Foe in Multi-Agent Games NIPS 2019
Write, Execute, Assess: Program Synthesis with a REPL NIPS 2019
Flexible neural representation for physics prediction NIPS 2018
Visual Object Networks: Image Generation with Disentangled 3D Representations NIPS 2018
End-to-End Differentiable Physics for Learning and Control NIPS 2018
Learning Libraries of Subroutines for Neurally–Guided Bayesian Program Induction NIPS 2018
Learning to Infer Graphics Programs from Hand-Drawn Images NIPS 2018
3D-Aware Scene Manipulation via Inverse Graphics NIPS 2018
Neural-Symbolic VQA: Disentangling Reasoning from Vision and Language Understanding NIPS 2018
Learning to Exploit Stability for 3D Scene Parsing NIPS 2018
Learning to Reconstruct Shapes from Unseen Classes NIPS 2018
Learning to Share and Hide Intentions using Information Regularization NIPS 2018
Shape and Material from Sound NIPS 2017
Self-Supervised Intrinsic Image Decomposition NIPS 2017
MarrNet: 3D Shape Reconstruction via 2.5D Sketches NIPS 2017
Learning to See Physics via Visual De-animation NIPS 2017
Hierarchical Deep Reinforcement Learning: Integrating Temporal Abstraction and Intrinsic Motivation NIPS 2016
Sampling for Bayesian Program Learning NIPS 2016
Probing the Compositionality of Intuitive Functions NIPS 2016
Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling NIPS 2016
Softstar: Heuristic-Guided Probabilistic Inference NIPS 2015
Galileo: Perceiving Physical Object Properties by Integrating a Physics Engine with Deep Learning NIPS 2015
Deep Convolutional Inverse Graphics Network NIPS 2015
Unsupervised Learning by Program Synthesis NIPS 2015
Risk and Regret of Hierarchical Bayesian Learners ICML 2015
Approximate Bayesian Image Interpretation using Generative Probabilistic Graphics Programs NIPS 2013
One-shot learning by inverting a compositional causal process NIPS 2013