Konrad P. Körding

Towards an integration of deep learning and neuroscience

2016 · bioRxiv (Cold Spring Harbor Laboratory)

Neuroscience has focused on the detailed implementation of computation, studying neural codes, dynamics and circuits. In machine learning, however, artificial neural networks tend to eschew precisely designed codes, dynamics or circuits in favor of brute …

What does it mean to understand a neural network?

2019 · arXiv (Cornell University)

We can define a neural network that can learn to recognize objects in less than 100 lines of code. However, after training, it is characterized by millions of weights that contain the knowledge about many …

Deep learning for brains?: Different linear and nonlinear scaling in UK Biobank brain images vs. machine-learning datasets

2019 · bioRxiv (Cold Spring Harbor Laboratory)

Abstract In recent years, deep learning has unlocked unprecedented success in various domains, especially in image, text, and speech processing. These breakthroughs may hold promise for neuroscience and especially for brain-imaging investigators who start to …