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11/25/2022
Solving math word problems with process- and outcome-based feedback
Recent work has shown that asking language models to generate reasoning ...
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02/08/2022
Competition-Level Code Generation with AlphaCode
Programming is a powerful and ubiquitous problem-solving tool. Developin...
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07/24/2020
Interpreting Spatially Infinite Generative Models
Traditional deep generative models of images and other spatial modalitie...
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02/28/2020
Inverse Graphics GAN: Learning to Generate 3D Shapes from Unstructured 2D Data
Recent work has shown the ability to learn generative models for 3D shap...
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02/17/2020
Learning Robust Representations via Multi-View Information Bottleneck
The information bottleneck principle provides an information-theoretic m...
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06/01/2018
Inverting Supervised Representations with Autoregressive Neural Density Models
Understanding the nature of representations learned by supervised machin...
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05/21/2018
Generative Adversarial Examples
Adversarial examples are typically constructed by perturbing an existing...
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12/02/2016
Summary - TerpreT: A Probabilistic Programming Language for Program Induction
We study machine learning formulations of inductive program synthesis; t...
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11/21/2016
A Deep Learning Approach for Joint Video Frame and Reward Prediction in Atari Games
Reinforcement learning is concerned with identifying reward-maximizing b...
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08/15/2016
TerpreT: A Probabilistic Programming Language for Program Induction
We study machine learning formulations of inductive program synthesis; g...
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08/09/2016
