Publications associées à From Kernel Methods to Neural Networks: A Unifying Variational Formulation

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Towards Stable and Efficient Adversarial Training against $l_1$ Bounded Adversarial Attacks

Sabine Süsstrunk, Mathieu Salzmann, Yulun Jiang, Chen Liu, Zhuoyi Huang

We address the problem of stably and efficiently training a deep neural network robust to adversarial perturbations bounded by an

l_1

norm. We demonstrate that achieving robustness against

l_1

-bounded perturbations is more challenging than in the

l_2

...

2023

From Kernel Methods to Neural Networks: A Unifying Variational Formulation

Graph Chatbot

Chattez avec Graph Search

Towards Robust Monitoring of the Laser Powder Bed Fusion Process based on Acoustic Emission combined with Machine Learning Solutions

Towards Stable and Efficient Adversarial Training against $l_1$ Bounded Adversarial Attacks

Linear Complexity Self-Attention With 3rd Order Polynomials

Optimizing in-situ monitoring for laser powder bed fusion process: Deciphering acoustic emission and sensor sensitivity with explainable machine learning

Visual question answering from another perspective: CLEVR mental rotation tests *

Explicit representations for Banach subspaces of Lizorkin distributions

Decentralized learning made easy with DecentralizePy

Robust direct acoustic impedance control using two microphones for mixed feedforward-feedback controller

A Comparison of Residual-based Methods on Fault Detection

Universal Approximation Property of Hamiltonian Deep Neural Networks

Explicit representations for Banach subspaces of Lizorkin distributions

Linear Complexity Self-Attention With 3rd Order Polynomials

Optimizing in-situ monitoring for laser powder bed fusion process: Deciphering acoustic emission and sensor sensitivity with explainable machine learning

Visual question answering from another perspective: CLEVR mental rotation tests *

Towards Stable and Efficient Adversarial Training against $l_1$ Bounded Adversarial Attacks

Decentralized learning made easy with DecentralizePy

Towards Robust Monitoring of the Laser Powder Bed Fusion Process based on Acoustic Emission combined with Machine Learning Solutions

A Comparison of Residual-based Methods on Fault Detection

Robust direct acoustic impedance control using two microphones for mixed feedforward-feedback controller

Universal Approximation Property of Hamiltonian Deep Neural Networks