Publication

Comparing transferability in neural network approaches and linear models for machine-learning interaction potentials

Related publications (50)

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.

Comparing transferability in neural network approaches and linear models for machine-learning interaction potentials

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

Random matrix methods for high-dimensional machine learning models

Efficient and insightful descriptors for representing molecular and material space

Thermal transport of glasses via machine learning driven simulations

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

Supervised learning and inference of spiking neural networks with temporal coding

Task-driven neural network models predict neural dynamics of proprioception

Machine-learned interatomic potentials: Recent developments and prospective applications

Quantification of the Phenomena Affecting Reflective Arterial Photoplethysmography

Local Kernel Regression and Neural Network Approaches to the Conformational Landscapes of Oligopeptides