3 citations · 3 across the 2 of their papers we have counts for
7 papers
Learning, fast and slow
Markus Meister
Animals can learn efficiently from a single experience and change their future behavior in response. However, in other instances, animals learn very slowly, requiring thousands of…
Curved Micro-Electrode Arrays
Markus Meister
Multi-electrode arrays serve to record electrical signals of many neurons in the brain simultaneously. For most of the past century, electrodes that penetrate brain tissue have had…
Fine-Grained System Identification of Nonlinear Neural Circuits
Dawna Bagherian, James Gornet, Jeremy Bernstein +3
We study the problem of sparse nonlinear model recovery of high dimensional compositional functions. Our study is motivated by emerging opportunities in neuroscience to recover fin…
Learning by Turning: Neural Architecture Aware Optimisation
Yang Liu, Jeremy Bernstein, Markus Meister +1
Descent methods for deep networks are notoriously capricious: they require careful tuning of step size, momentum and weight decay, and which method will work best on a new benchmar…
Learning compositional functions via multiplicative weight updates
Jeremy Bernstein, Jiawei Zhao, Markus Meister +3
Compositionality is a basic structural feature of both biological and artificial neural networks. Learning compositional functions via gradient descent incurs well known problems l…
PanDA: Panoptic Data Augmentation
Yang Liu, Pietro Perona, Markus Meister
The recently proposed panoptic segmentation task presents a significant challenge of image understanding with computer vision by unifying semantic segmentation and instance segment…