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Ilya Kuzovkin | Brain-Computer Interfaces, Machine Learning, Neuroscience

Brain-Computer Interfaces, Machine Learning, Neuroscience. Notes on NIPS 2016. Neural Information Processing Systems (NIPS) conference is a place where computational neuroscience meets machine learning. Due to the rise of deep learning …. Using a MindMap in Informal DNN Parameter Optimization. So you’ve decided to throw a Deep Neural Network at your data. Great! You try a basic setup and it kinda works, …. Notes on ICML 2016. Notes on BCI Meeting 2016. Article overview: Unsupervised Learning of Visual St...

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Ilya Kuzovkin | Brain-Computer Interfaces, Machine Learning, Neuroscience | ikuz.eu Reviews

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Brain-Computer Interfaces, Machine Learning, Neuroscience. Notes on NIPS 2016. Neural Information Processing Systems (NIPS) conference is a place where computational neuroscience meets machine learning. Due to the rise of deep learning …. Using a MindMap in Informal DNN Parameter Optimization. So you’ve decided to throw a Deep Neural Network at your data. Great! You try a basic setup and it kinda works, …. Notes on ICML 2016. Notes on BCI Meeting 2016. Article overview: Unsupervised Learning of Visual St...

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Ilya Kuzovkin | Brain-Computer Interfaces, Machine Learning, Neuroscience | ikuz.eu Reviews

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Brain-Computer Interfaces, Machine Learning, Neuroscience. Notes on NIPS 2016. Neural Information Processing Systems (NIPS) conference is a place where computational neuroscience meets machine learning. Due to the rise of deep learning …. Using a MindMap in Informal DNN Parameter Optimization. So you’ve decided to throw a Deep Neural Network at your data. Great! You try a basic setup and it kinda works, …. Notes on ICML 2016. Notes on BCI Meeting 2016. Article overview: Unsupervised Learning of Visual St...

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Article overview: Unsupervised Learning of Visual Structure Using Predictive Generative Networks

http://ikuz.eu/2015/12/02/article-overview-unsupervised-learning-of-visual-structure-using-predictive-generative-networks

Brain-Computer Interfaces, Machine Learning, Neuroscience. Article overview: Unsupervised Learning of Visual Structure Using Predictive Generative Networks. December 2, 2015. Article overview: Unsupervised Learning of Visual Structure Using Predictive Generative Networks. Did you like this article? Share it with your friends! Leave a Reply Cancel reply. Your email address will not be published. You may use these. Powered by Pinboard Theme.

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pyactivetwo for the BioSemi ActiveTwo EEG device

http://ikuz.eu/2015/06/22/pyactivetwo-for-the-biosemi-activetwo-eeg-device

Brain-Computer Interfaces, Machine Learning, Neuroscience. Pyactivetwo for the BioSemi ActiveTwo EEG device. June 22, 2015. Recently I’ve been working with the BioSemi. EEG device. This post. Gives an example of how to read the raw data into Python using TCP packets. To make it more comfortable for the next generations I packed the core functionality into a python package pyactivetwo. You can download that via. And contribute on GitHub. Did you like this article? Share it with your friends!

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Notes on BCI Meeting 2016

http://ikuz.eu/2016/06/03/notes-on-bci-meeting-2016

Brain-Computer Interfaces, Machine Learning, Neuroscience. Notes on BCI Meeting 2016. June 3, 2016. I had two personal goals for attending BCI Meeting 2016. Present my poster, gather feedback and look for contacts with whom the idea presented on the poster might be tested on intracranial devices. Figure out if there is a future for BCI beyond its medical applications. Eb Fetz, Emanual Donchin, Jon Wolpaw. History and Future of BCI. Historical overviews, predictions. It seems that all of the important ach...

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CNS 2015 in Prague: Notes

http://ikuz.eu/2015/07/22/cns-2015-in-prague-notes

Brain-Computer Interfaces, Machine Learning, Neuroscience. CNS 2015 in Prague: Notes. July 22, 2015. 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 I was eager to see how NS could benefit. This post served as a notebook during the conference and is biased towards trying to find applications of DL in the field of NS. Learning and variability in birdsong. Wilson-Cowan Equations for Neocortical Dynamics.

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Deep Learning: Theory, History, State of the Art & Practical Tools

http://ikuz.eu/2016/01/20/deep-learning-theory-history-state-of-the-art-practical-tools

Brain-Computer Interfaces, Machine Learning, Neuroscience. Deep Learning: Theory, History, State of the Art and Practical Tools. January 20, 2016. Deep Learning: Theory, History, State of the Art and Practical Tools. An introductory talk about deep learning given at Machine Learning Estonia meetup. Did you like this article? Share it with your friends! Leave a Reply Cancel reply. Your email address will not be published. You may use these. Powered by Pinboard Theme.

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Four Years Remaining » Blog Archive » My Favourite Statistical Method

http://fouryears.eu/2015/04/05/my-favourite-statistical-method

My Favourite Statistical Method. I guess life of a statistician was probably way simpler back in the days when you could run a couple of t-tests. In the particular context of feature selection. My appreciation of it stems from my background in bioinformatics and some experience with motif detection. In particular. Suppose you have measured the DNA sequences for a bunch of genes. What can you do to learn something new about the sequence structure from that data? One of your best bets is to first. On top) ...

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Four Years Remaining » Bioinformatics

http://fouryears.eu/tags/bioinformatics

Two Bananas Make a Human. There is a popular claim. That "human DNA is 50% similar to the DNA of a banana", which is often cited in the context of "science popularization" as well as in the various " OMG did you know that. Articles. It sounds funny, scientific and "plausible", hence I've seen many smart people repeat it, perhaps as a joke, without giving it too much thought. It is worth giving a thought, though. If you change 50% of human DNA you can obtain the DNA of a banana. At this point some passion...

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Four Years Remaining » Statistics

http://fouryears.eu/tags/statistics

Bayesian Statistics in Layman's Terms. This is a (slightly updated) repost of my quora answer. To the corresponding question. There are many ways. In which smart people tend to explain Bayesian statistics and contrast it with a "non-Bayesian" one. One usually highlights that the primary concept of a Bayesian approach is the the desire to model everything as a probability distribution. Once this is fact is clear, many smart people would proceed to claim that this. Bayesian "thinking" tends to be more flex...

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Four Years Remaining » Tool

http://fouryears.eu/tags/tool

While writing the previous post. I was thinking of coming up with a small fun illustration for Aframe. I first heard about AFrame at the recent European Innovation Academy. A team-project-based entrepreneurship summer school. The team called MemVee. I am a visual learner myself and understand the importance of such illustrations. In fact, I try to use and preach graphical references in my teaching practice whenever I find the time and opportunity:. For the computer graphics course. Unfortunately the mate...

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Ilya Kuzovkin | Brain-Computer Interfaces, Machine Learning, Neuroscience

Brain-Computer Interfaces, Machine Learning, Neuroscience. Notes on NIPS 2016. Neural Information Processing Systems (NIPS) conference is a place where computational neuroscience meets machine learning. Due to the rise of deep learning …. Using a MindMap in Informal DNN Parameter Optimization. So you’ve decided to throw a Deep Neural Network at your data. Great! You try a basic setup and it kinda works, …. Notes on ICML 2016. Notes on BCI Meeting 2016. Article overview: Unsupervised Learning of Visual St...

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