Bernd Albert Illing

Cette personne n’est plus à l’EPFL

À propos
Confidentialité
Mentions légales

Graph Chatbot

Publications associées (4)

NMDA-driven dendritic modulation enables multitask representation learning in hierarchical sensory processing pathways

Walter Senn, Willem Anna Mark Wybo, Matthias Chinyen Tsai, Bernd Albert Illing

While sensory representations in the brain depend on context, it remains unclear how such modulations are implemented at the biophysical level, and how processing layers further in the hierarchy can extract useful features for each possible contex-tual sta ...

National Academy of Sciences2023

Biologically plausible unsupervised learning in shallow and deep neural networks

Bernd Albert Illing

The way our brain learns to disentangle complex signals into unambiguous concepts is fascinating but remains largely unknown. There is evidence, however, that hierarchical neural representations play a key role in the cortex. This thesis investigates biolo ...

EPFL2021

Local plasticity rules can learn deep representations using self-supervised contrastive predictions

Wulfram Gerstner, Jean Ventura, Bernd Albert Illing

Learning in the brain is poorly understood and learning rules that respect biological constraints, yet yield deep hierarchical representations, are still unknown. Here, we propose a learning rule that takes inspiration from neuroscience and recent advances ...

2021

Biologically plausible deep learning – but how far can we go with shallow networks?

Wulfram Gerstner, Johanni Michael Brea, Bernd Albert Illing

Training deep neural networks with the error backpropagation algorithm is considered implausible from a biological perspective. Numerous recent publications suggest elaborate models for biologically plausible variants of deep learning, typically defining s ...

2019

Page 1 sur 1