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Explore Volterra Series in machine learning, reducing sample and model complexity while maintaining high performance in inference problems.
Explore conformal inference methods for exact prediction intervals, covering basic principles and recent advancements in quantitative and categorical label applications.
Explore wavelets' role in modeling vision, extracting brain activity patterns, and detecting neural markers of attention. Learn how machines can measure attention for novel human communication methods.
Explore deep neural networks' ability to reveal geometry, topology, and discrete symmetries in manifolds. Learn about universal approximators and their applications in inverse problems and group actions.
Explore revolutionary image denoising techniques, their applications in inverse problems, and the concept of diverse solutions in image processing.
Explore an innovative Markov chain Monte Carlo algorithm combining global proposals and mobile moves for efficient, parallelizable sampling in various applications.
Explore deep learning's progress, challenges, and theoretical foundations. Gain insights into the geometric interpretation of deep networks and spline approximation, with a focus on Scattering Networks.
Explore the evolving landscape of computational analysis, signal processing, and machine learning. Gain insights on bridging the gap between mathematical and digital communities.
Explore multiscale basis dictionaries and scattering networks on simplicial complexes, focusing on HGLET and GHWT. Learn applications in coauthorship/citation complex and article classification.
Explore supervised learning algorithms' strengths and weaknesses, comparing k-nearest-neighbor, kernel methods, and neural networks for adaptivity and performance across various problems.
Explore methods for interpreting neural networks, including contextual decomposition and adaptive wavelet distillation, to enhance model trustworthiness and performance.
Explore image processing advancements using machine learning, focusing on implicit priors in neural networks for tasks like denoising, deblurring, and super-resolution.
Explore the profound impact of Stephane's intellectual contributions to auditory neuroscience, from cochlear encoding to cortical processing.
Découvrez les mathématiques avec Hugo Duminil-Copin, médaillé Fields 2022, lors d'une rencontre captivante avec des lycéens de l'Essonne.
Explore ultrarelativistic gravitational scattering, its developments in (super)gravity and string theory, and applications to gravitational binaries.
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