Lists (9)
Stars
The most cited deep learning papers
Latex code for making neural networks diagrams
Classical equations and diagrams in machine learning
LaTeX files for the Deep Learning book notation
An open-source, customizable intermediate logic textbook
Book in preparation: introduction to theoretical computer science
Rough working notes on neural networks
We cherry-pick the most understandable explanations and definitions into one summary to summarize the content of the lecture about Machine Learning of Prof. Joachim Buhmann.
a repository containing everything relevant to our fast non-negative deconvolution work
Summary of the ETH INI Introduction to Neuroinformatics course.
Summary of the ETH INI course Neuromorphic Engineering 1 (NE1)
We cherry-pick the most understandable explanations and definitions into one summary to summarize the content of the lecture about Machine Learning of Prof. Joachim Buhmann.
Summary of the ZNZ - HS16 Introductory Course in Neuroscience - Fall 2016
Summary of a course called Neurophysics(227-1038-00L) at ETH Zürich taught by R. Hahnloser, J.-P. Pfister
summary of the lectures about Grapht Theory ministred by Prof. Dr. Benjamin Sudakov with additional references.
Simple task training a head-fixed mouse to run on a wheel