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All publications by Josh Tenenbaum
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Risk and Regret of Hierarchical Bayesian Learners
Jonathan Huggins and Josh Tenenbaum
Proceedings of the 32nd International Conference on Machine Learning (ICML-15), 2015


Softstar: Heuristic-Guided Probabilistic Inference
Mathew Monfort, Brenden M. Lake, Brenden M. Lake, Brian Ziebart, Patrick Lucey and Josh Tenenbaum
Advances in Neural Information Processing Systems 28, 2015


Deep Convolutional Inverse Graphics Network
Tejas D. Kulkarni, William F. Whitney, Pushmeet Kohli and Josh Tenenbaum
Advances in Neural Information Processing Systems 28, 2015


Unsupervised Learning by Program Synthesis
Kevin Ellis, Armando Solar-lezama and Josh Tenenbaum
Advances in Neural Information Processing Systems 28, 2015


Galileo: Perceiving Physical Object Properties by Integrating a Physics Engine with Deep Learning
Jiajun Wu, Ilker Yildirim, Joseph J. Lim, Bill Freeman and Josh Tenenbaum
Advances in Neural Information Processing Systems 28, 2015


One-shot learning by inverting a compositional causal process
Brenden M. Lake, Ruslan Salakhutdinov and Josh Tenenbaum
Advances in Neural Information Processing Systems 26, 2013


Approximate Bayesian Image Interpretation using Generative Probabilistic Graphics Programs
Vikash Mansinghka, Tejas D. Kulkarni, Yura N. Perov and Josh Tenenbaum
Advances in Neural Information Processing Systems 26, 2013


Infinite Dynamic Bayesian Networks
Finale Doshi, David Wingate, Josh Tenenbaum and Nicholas Roy
Proceedings of the 28th International Conference on Machine Learning (ICML-11), 2011