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08/08/2023
PUG: Photorealistic and Semantically Controllable Synthetic Data for Representation Learning
Synthetic image datasets offer unmatched advantages for designing and ev...
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07/24/2023
Does Progress On Object Recognition Benchmarks Improve Real-World Generalization?
For more than a decade, researchers have measured progress in object rec...
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04/24/2023
A Cookbook of Self-Supervised Learning
Self-supervised learning, dubbed the dark matter of intelligence, is a p...
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04/11/2023
Pinpointing Why Object Recognition Performance Degrades Across Income Levels and Geographies
Despite impressive advances in object-recognition, deep learning systems...
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12/09/2022
A Whac-A-Mole Dilemma: Shortcuts Come in Multiples Where Mitigating One Amplifies Others
Machine learning models have been found to learn shortcuts – unintended ...
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11/03/2022
ImageNet-X: Understanding Model Mistakes with Factor of Variation Annotations
Deep learning vision systems are widely deployed across applications whe...
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10/24/2022
The Robustness Limits of SoTA Vision Models to Natural Variation
Recent state-of-the-art vision models introduced new architectures, lear...
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10/24/2022
Robust Self-Supervised Learning with Lie Groups
Deep learning has led to remarkable advances in computer vision. Even so...
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10/13/2022
Disentanglement of Correlated Factors via Hausdorff Factorized Support
A grand goal in deep learning research is to learn representations capab...
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09/02/2021
CrypTen: Secure Multi-Party Computation Meets Machine Learning
Secure multi-party computation (MPC) allows parties to perform computati...
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06/09/2021
Grounding inductive biases in natural images:invariance stems from variations in data
To perform well on unseen and potentially out-of-distribution samples, i...
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02/10/2021
Addressing the Topological Defects of Disentanglement via Distributed Operators
A core challenge in Machine Learning is to learn to disentangle natural ...
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02/06/2019
Global Explanations of Neural Networks: Mapping the Landscape of Predictions
A barrier to the wider adoption of neural networks is their lack of inte...
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12/23/2018
Mixed Membership Recurrent Neural Networks
Models for sequential data such as the recurrent neural network (RNN) of...
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11/15/2018
