Publication

Combining biophysical models and machine learning to optimize implant geometry and stimulation protocol for intraneural electrodes

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.

Publications related to Combining biophysical models and machine learning to optimize implant geometry and stimulation protocol for intraneural electrodes | EPFL Graph Search

Combining biophysical models and machine learning to optimize implant geometry and stimulation protocol for intraneural electrodes

Graph Chatbot

Chat with Graph Search

Biophysically accurate and machine learning-based surrogate models to optimize neuroprosthesis design and operation

Non-invasive stimulation of the human striatum disrupts reinforcement learning of motor skills

A method and system for optimizing design, implantation, and stimulation protocols of electrodes stimulating the nervous system

Decoding electroencephalographic responses to visual stimuli compatible with electrical stimulation

Machine Learning for Modeling Stock Returns

Modeling, fabrication and validation of 3D neural interfaces for peripheral nerves and brain organoids

Driving and suppressing the human language network using large language models

Random matrix methods for high-dimensional machine learning models

Partial discharge localization in power transformer tanks using machine learning methods

Reduced Training Data for Laser Ultrasound Signal Interpretation by Neural Networks