Publication

Inverse Modelling and Predictive Inference in Continuum Mechanics: a Data-Driven Approach

Related publications (207)

About
Privacy
Disclaimer

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

Inverse Modelling and Predictive Inference in Continuum Mechanics: a Data-Driven Approach

Graph Chatbot

Chat with Graph Search

Task-driven neural network models predict neural dynamics of proprioception: Experimental data, activations and predictions of neural network models

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

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

Generalization of Scaled Deep ResNets in the Mean-Field Regime

Reduced Training Data for Laser Ultrasound Signal Interpretation by Neural Networks

Explainable Fault Diagnosis of Oil-Immersed Transformers: A Glass-Box Model

M2SKD: Multi-to-Single Knowledge Distillation of Real-Time Epileptic Seizure Detection for Low-Power Wearable Systems

DeepBND: A machine learning approach to enhance multiscale solid mechanics

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

Deep Learning Generalization with Limited and Noisy Labels