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12/13/2022
What do Vision Transformers Learn? A Visual Exploration
Vision transformers (ViTs) are quickly becoming the de-facto architectur...
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10/19/2022
Canary in a Coalmine: Better Membership Inference with Ensembled Adversarial Queries
As industrial applications are increasingly automated by machine learnin...
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08/19/2022
Cold Diffusion: Inverting Arbitrary Image Transforms Without Noise
Standard diffusion models involve an image transform – adding Gaussian n...
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02/11/2022
End-to-end Algorithm Synthesis with Recurrent Networks: Logical Extrapolation Without Overthinking
Machine learning systems perform well on pattern matching tasks, but the...
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08/13/2021
Datasets for Studying Generalization from Easy to Hard Examples
We describe new datasets for studying generalization from easy to hard e...
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08/03/2021
Where do Models go Wrong? Parameter-Space Saliency Maps for Explainability
Conventional saliency maps highlight input features to which neural netw...
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06/08/2021
Can You Learn an Algorithm? Generalizing from Easy to Hard Problems with Recurrent Networks
Deep neural networks are powerful machines for visual pattern recognitio...
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03/02/2021
DP-InstaHide: Provably Defusing Poisoning and Backdoor Attacks with Differentially Private Data Augmentations
Data poisoning and backdoor attacks manipulate training data to induce s...
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11/18/2020