Publications associées à Optimization and Generalization of Shallow Neural Networks with Quadratic Activation Functions

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Optimization and Generalization of Shallow Neural Networks with Quadratic Activation Functions

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Deep Learning Theory Through the Lens of Diagonal Linear Networks

Generalization of Scaled Deep ResNets in the Mean-Field Regime

Task-driven neural network models predict neural dynamics of proprioception: Experimental data, activations and predictions of neural network models

Gibbs sampling the posterior of neural networks

Performing and Detecting Backdoor Attacks on Face Recognition Algorithms

Sparse autoregressive neural networks for classical spin systems

Leveraging Continuous Time to Understand Momentum When Training Diagonal Linear Networks

Detecting Road Obstacles by Erasing Them

Deep Learning Generalization with Limited and Noisy Labels

Hamiltonian Deep Neural Networks Guaranteeing Non-Vanishing Gradients by Design

Deep Learning Theory Through the Lens of Diagonal Linear Networks

Generalization of Scaled Deep ResNets in the Mean-Field Regime

Sparse autoregressive neural networks for classical spin systems

Task-driven neural network models predict neural dynamics of proprioception: Experimental data, activations and predictions of neural network models

Leveraging Continuous Time to Understand Momentum When Training Diagonal Linear Networks

Deep Learning Generalization with Limited and Noisy Labels

Hamiltonian Deep Neural Networks Guaranteeing Non-Vanishing Gradients by Design

Performing and Detecting Backdoor Attacks on Face Recognition Algorithms

Gibbs sampling the posterior of neural networks

Detecting Road Obstacles by Erasing Them