research
∙
05/30/2023
Synaptic Weight Distributions Depend on the Geometry of Plasticity
Most learning algorithms in machine learning rely on gradient descent to...
share
research
∙
12/16/2022
Efficient Conditionally Invariant Representation Learning
We introduce the Conditional Independence Regression CovariancE (CIRCE),...
research
∙
06/22/2021
Towards Biologically Plausible Convolutional Networks
Convolutional networks are ubiquitous in deep learning. They are particu...
research
∙
06/15/2021
Self-Supervised Learning with Kernel Dependence Maximization
We approach self-supervised learning of image representations from a sta...
research
∙
06/12/2020
Kernelized information bottleneck leads to biologically plausible 3-factor Hebbian learning in deep networks
The state-of-the art machine learning approach to training deep neural n...
research
∙
10/23/2019
Working memory facilitates reward-modulated Hebbian learning in recurrent neural networks
Reservoir computing is a powerful tool to explain how the brain learns t...
research
∙
03/19/2019
