The aim of this work is to compare different machine learning algorithms in an attempt to find the best one for classifying EEG data. In…
Deep Learning: Theory, History, State of the Art & Practical Tools from Ilya Kuzovkin An introductory talk about deep learning given at Machine Learning Estonia…
Article overview: Unsupervised Learning of Visual Structure Using Predictive Generative Networks from Ilya Kuzovkin This set of slides goes over the recent article that tries…
Article overview: Deep Neural Networks Reveal a Gradient in the Complexity of Neural Representations across the Ventral Stream from Ilya Kuzovkin The article presents the…
“Introduction to Computational Neuroscience” is the flagship course offered by Computational Neuroscience Lab at the Institute of Computer Science of University of Tartu. From the…
Download PDF: https://ilyakuzovkin.com/identity/Ilya_Kuzovkin_CV.pdf
Caffe is a framework for deep learning. In a deep learning net it is quite hard to find good parameters (learning rate, dropout, size of…
Right after ICML 2015 I got to visit Computational Neuroscience meeting in Prague. Impressed by the advances in deep learning and AI field in general…
This thesis describes an SSVEP-based BCI implemented as a practical part of this work. One possible usage of a BCI that efficiently implements a communication…
Recently I’ve been working with the BioSemi ActiveTwo EEG device. This post gives an example of how to read the raw data into Python using…
While reading “An Introduction to the Conjugate Gradient Method Without the Agonizing Pain” I decided to boost understand by repeating the story told there in…
DeepMind explored a bit further their Atari-plaing AI and published an article in Nature. Along with the article comes the source code which I ran…