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Batch normalization

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Batch normalization

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Fast Adversarial Training With Adaptive Step Size

ADAGRAD Avoids Saddle Points

ADAGRAD Avoids Saddle Points

Robust Binary Models by Pruning Randomly-initialized Networks

Approximating Relu Networks By Single-Spike Computation

OptTTA: Learnable Test-Time Augmentation for Source-Free Medical Image Segmentation Under Domain Shift

Distributed neural network control with dependability guarantees: a compositional port-Hamiltonian approach

Phase diagram of Stochastic Gradient Descent in high-dimensional two-layer neural networks

Adversarial training with informed data selection

On Smoothed Explanations: Quality and Robustness

Fast Adversarial Training With Adaptive Step Size

On Smoothed Explanations: Quality and Robustness

Phase diagram of Stochastic Gradient Descent in high-dimensional two-layer neural networks

ADAGRAD Avoids Saddle Points

Robust Binary Models by Pruning Randomly-initialized Networks

Adversarial training with informed data selection

ADAGRAD Avoids Saddle Points

OptTTA: Learnable Test-Time Augmentation for Source-Free Medical Image Segmentation Under Domain Shift

Distributed neural network control with dependability guarantees: a compositional port-Hamiltonian approach

Approximating Relu Networks By Single-Spike Computation