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Sven Gowal

A Fine-Grained Analysis on Distribution Shift
A fine-grained analysis of robustness to distribution shifts
Make Sure You're Unsure: A Framework for Verifying Probabilistic Specifications
A framework for robustness certification of smoothed classifiers using f-divergences
Achieving robustness in the wild via adversarial mixing with disentangled representations
Efficient neural network verification with exactness characterization
The Autoencoding Variational Autoencoder
Towards Verified Robustness under Text Deletion Interventions
A Dual Approach to Verify and Train Deep Networks.
Achieving verified robustness to symbol substitutions via interval bound propagation
Adversarial robustness through local linearization
Scalable verified training for provably robust image classification
Toward evaluating robustness of deep reinforcement learning with continuous control
Verification of non-linear specifications for neural networks
A dual approach to scalable verification of deep networks

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