Robust Data-Driven Dynamic Programming

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We consider the problem of learning a target function corresponding to a deep, extensive-width, non-linear neural network with random Gaussian weights. We consider the asymptotic limit where the number of samples, the input dimension and the network width ...

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The HST treasury programme BUFFALO provides extended wide-field imaging of the six Hubble Frontier Fields galaxy clusters. Here we present the combined strong and weak-lensing analysis of Abell 370, a massive cluster at z = 0.375. From the reconstructed to ...

Robust Data-Driven Dynamic Programming

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Personalized Privacy-Preserving Distributed Learning on Heterogeneous Data

Bayes-optimal Learning of Deep Random Networks of Extensive-width

Robust machine learning for neuroscientific inference

Stability: a search for structure

Dated: Guidelines for Creating Synthetic Datasets for Engineering Design Applications

DATA-DRIVEN INVERSE DESIGN METHOD FOR TURBOMACHINERY

Generalization and Personalization of Machine Learning for Multimodal Mobile Sensing in Everyday Life

Improving Object Detection under Domain Shifts

Spectral Estimators for High-Dimensional Matrix Inference

Euclid preparation: XXVIII. Forecasts for ten different higher-order weak lensing statistics

Data set for control of Ge island coalescence for the formation of nanowires on silicon

Efficient Online Clustering with Moving Costs

Accurate and agile flight with winged drones

Beyond the ultradeep frontier fields and legacy observations (BUFFALO): a high-resolution strong plus weak-lensing view of Abell 370