Publication

Neural networks as mechanisms to regulate division of labor

Related publications (39)

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.

Neural networks as mechanisms to regulate division of labor

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

Rapid Network Adaptation: Learning to Adapt Neural Networks Using Test-Time Feedback

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

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

Learning of Continuous and Piecewise-Linear Functions With Hessian Total-Variation Regularization

Estimating muscle activation from EMG using deep learning-based dynamical systems models

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

Artificial Neural Network Approach to the Analytic Continuation Problem

Spiking Neural Networks Trained With Backpropagation For Low Power Neuromorphic Implementation Of Voice Activity Detection

How single neuron properties shape chaotic dynamics and signal transmission in random neural networks