Chaining Meets Chain Rule: Multilevel Entropic Regularization and Training of Neural Networks

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We present a finite elements-neural network approach for the numerical approximation of parametric partial differential equations. The algorithm generates training data from finite element simulations, and uses a data -driven (supervised) feedforward neura ...

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Chaining Meets Chain Rule: Multilevel Entropic Regularization and Training of Neural Networks

Chattez avec Graph Search

Error assessment of an adaptive finite elements-neural networks method for an elliptic parametric PDE

Feature-based encoding of face identity by single neurons in the human amygdala and hippocampus

Task-driven neural network models predict neural dynamics of proprioception: Neural network model weights

Domain shift, domain adaptation, and generalization: A focus on MRI

Self-supervised and few-shot learning for robust bioaerosol monitoring

Robust machine learning for neuroscientific inference

Posterior-Based Analysis of Spatio-Temporal Features for Sign Language Assessment

Optimizing Dynamic Aperture Studies with Active Learning

A graph convolutional autoencoder approach to model order reduction for parametrized PDEs

ThermoNeRF: A multimodal Neural Radiance Field for joint RGB-thermal novel view synthesis of building facades

Sparse autoregressive neural networks for classical spin systems

DEMO: Dielectric elastomer actuators (DEAs) for the restoration of facial movements

33.3 MiBMI: A 192/512-Channel 2.46mm² Miniaturized Brain-Machine Interface Chipset Enabling 31-Class Brain-to-Text Conversion Through Distinctive Neural Codes

Probing the latent hierarchical structure of data via diffusion models

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

What can radars tell us about snowfall microphysics? Insights from a Markov chain Monte-Carlo approach

Enabling Uncertainty Estimation in Iterative Neural Networks

Machine-learning-empowered FDTD/FEM simulations for predictive solar energy absorption in plasmonic metamaterial nanocavity arrays

Aggregating Spatial and Photometric Context for Photometric Stereo

Context selectivity with dynamic availability enables lifelong continual learning