Riemannian geometry applied to time series: application to brain signal prediction and transfer learning En savoir plus sur Riemannian geometry applied to time series: application to brain signal prediction and transfer learning
From Alexnet to Transformers: Measuring the Non-linearity of Deep Neural Networks with Affine Optimal Transport En savoir plus sur From Alexnet to Transformers: Measuring the Non-linearity of Deep Neural Networks with Affine Optimal Transport
Classification de processus de Hawkes multivariés en grande dimension En savoir plus sur Classification de processus de Hawkes multivariés en grande dimension
Supervised Learning with missing values: theoretical foundations and practical guidelines. En savoir plus sur Supervised Learning with missing values: theoretical foundations and practical guidelines.
Sparse inference in Poisson Log-Normal model by approximating the L0-norm En savoir plus sur Sparse inference in Poisson Log-Normal model by approximating the L0-norm
Analytic inference with separately exchangeable data En savoir plus sur Analytic inference with separately exchangeable data
Online Multivariate Changepoint Detection: Leveraging Links With Computational Geometry En savoir plus sur Online Multivariate Changepoint Detection: Leveraging Links With Computational Geometry
Designing Learning Machines for industrial Applications: from Transfer Learning to Physics Informed Machine Learning Models. En savoir plus sur Designing Learning Machines for industrial Applications: from Transfer Learning to Physics Informed Machine Learning Models.