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12/24/2022
GraphCast: Learning skillful medium-range global weather forecasting
We introduce a machine-learning (ML)-based weather simulator–called "Gra...
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12/06/2021
Noether Networks: Meta-Learning Useful Conserved Quantities
Progress in machine learning (ML) stems from a combination of data avail...
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09/22/2020
Tailoring: encoding inductive biases by optimizing unsupervised objectives at prediction time
From CNNs to attention mechanisms, encoding inductive biases into neural...
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03/11/2020
Meta-learning curiosity algorithms
We hypothesize that curiosity is a mechanism found by evolution that enc...
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10/01/2019
Omnipush: accurate, diverse, real-world dataset of pushing dynamics with RGB-D video
Pushing is a fundamental robotic skill. Existing work has shown how to e...
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04/18/2019
Graph Element Networks: adaptive, structured computation and memory
We explore the use of graph neural networks (GNNs) to model spatial proc...
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12/19/2018
Modular meta-learning in abstract graph networks for combinatorial generalization
Modular meta-learning is a new framework that generalizes to unseen data...
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06/26/2018
Modular meta-learning
Many prediction problems, such as those that arise in the context of rob...
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05/08/2018
Finding Frequent Entities in Continuous Data
In many applications that involve processing high-dimensional data, it i...
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10/03/2017
