research
∙
07/31/2023
A theory of data variability in Neural Network Bayesian inference
Bayesian inference and kernel methods are well established in machine le...
share
research
∙
05/12/2023
Optimal signal propagation in ResNets through residual scaling
Residual networks (ResNets) have significantly better trainability and t...
research
∙
02/10/2022
Decomposing neural networks as mappings of correlation functions
Understanding the functional principles of information processing in dee...
research
∙
12/10/2021
Unified Field Theory for Deep and Recurrent Neural Networks
Understanding capabilities and limitations of different network architec...
research
∙
10/13/2020
Unfolding recurrence by Green's functions for optimized reservoir computing
Cortical networks are strongly recurrent, and neurons have intrinsic tem...
research
∙
12/02/2019
