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A Bayesian data assimilation framework for lake 3D hydrodynamic models with a physics-preserving particle filtering method using SPUX-MITgcm v1

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A Bayesian data assimilation framework for lake 3D hydrodynamic models with a physics-preserving particle filtering method using SPUX-MITgcm v1

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Sparse autoregressive neural networks for classical spin systems

Statistical Inference for Inverse Problems: From Sparsity-Based Methods to Neural Networks

Coupling a recurrent neural network to SPAD TCSPC systems for real-time fluorescence lifetime imaging

Supervised learning and inference of spiking neural networks with temporal coding

From Probability Graphical Models to Dynamic Networks — A Bayesian perspective on Smooth Best Estimate of Trajectory with applications in Geodetic Engineering

Fundamental Limits in Statistical Learning Problems: Block Models and Neural Networks

The autoregressive neural network architecture of the Boltzmann distribution of pairwise interacting spins systems

Short-term runoff forecasting in an alpine catchment with a long short-term memory neural network

Bayesian Inversion for Nonlinear Imaging Models Using Deep Generative Priors

A Machine Learning-based Framework for Forecasting Sales of New Products With Short Life Cycles Using Deep Neural Networks