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Evan Archer

Black-box variational state space models. Centered Dirichlet Mixture (CDM) Entropy Estimator. Pitman-Yor Mixture (PYM) Entropy Estimator. I’m Evan Archer, a researcher in the Department of Statistics. I work on research problems at the intersection of computational neuroscience, statistics, and machine learning. When I’m not pondering math and science I’m a big fan of travel, novels, running, and riding and building bicycles. First initial)(last name) at utexas dot edu.

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Black-box variational state space models. Centered Dirichlet Mixture (CDM) Entropy Estimator. Pitman-Yor Mixture (PYM) Entropy Estimator. I’m Evan Archer, a researcher in the Department of Statistics. I work on research problems at the intersection of computational neuroscience, statistics, and machine learning. When I’m not pondering math and science I’m a big fan of travel, novels, running, and riding and building bicycles. First initial)(last name) at utexas dot edu.
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Evan Archer | evanarcher.com Reviews

https://evanarcher.com

Black-box variational state space models. Centered Dirichlet Mixture (CDM) Entropy Estimator. Pitman-Yor Mixture (PYM) Entropy Estimator. I’m Evan Archer, a researcher in the Department of Statistics. I work on research problems at the intersection of computational neuroscience, statistics, and machine learning. When I’m not pondering math and science I’m a big fan of travel, novels, running, and riding and building bicycles. First initial)(last name) at utexas dot edu.

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memming.wordpress.com memming.wordpress.com

10th Black Board Day (BBD10) | Memming

https://memming.wordpress.com/2015/05/07/10th-black-board-day-bbd10

10th Black Board Day (BBD10). On May 2nd 2015, I organized yet another BlackBoardDay. This time in New York City (on Columbia University campus, thanks Evan. I started the discussion by tracing the history of modern mathematics back to Gottlob Frege. Vika pointed out the axiomatic tradition goes back to Euclid (300 BC) . The first symbolic logic system powerful enough for mathematics (1879). Giuseppe Peano’s axiomatization of arithmetic (1889). David Hilbert’s program. Kurt Gödel was born! But then 2c is...

mackelab.org mackelab.org

News - mackelab@caesar

http://www.mackelab.org/blog/index.html

Deep Learning Summer School. From August 1st to 7th, Jan-Matthis is attending the deep learning summer school. In Montreal, organized by the Canadian Institute For Advanced Research. Today Poornima Ramesh joined our group for an internship, on a DAAD Rise Scholarship. Welcome on board Poornima! Granted us a Titan X GPU for faster training of deep neural networks for analyzing behavioural data. Many thanks to NVIDIA, as well to Jan-Matthis. For helping write the application. And awarded a scholarship.

mackelab.org mackelab.org

News - mackelab@caesar

http://www.mackelab.org/blog

Deep Learning Summer School. From August 1st to 7th, Jan-Matthis is attending the deep learning summer school. In Montreal, organized by the Canadian Institute For Advanced Research. Today Poornima Ramesh joined our group for an internship, on a DAAD Rise Scholarship. Welcome on board Poornima! Granted us a Titan X GPU for faster training of deep neural networks for analyzing behavioural data. Many thanks to NVIDIA, as well to Jan-Matthis. For helping write the application. And awarded a scholarship.

github.com github.com

earcher (Evan Archer) · GitHub

https://github.com/earcher

New York City, New York, USA. Http:/ www.evanarcher.com. Oct 28, 2011. Black box variational inference for state space models. Reference implementation of the NVIL algorithm for a simple Gaussian Mixture Model. Theano code for learning Sigmoid Belief Networks with variational inference. 22 contributions in the last year. Summary of pull requests, issues opened, and commits. Learn how we count contributions. Earcher has no activity during this period. You can't perform that action at this time.

scalablemodels.wordpress.com scalablemodels.wordpress.com

March | 2014 | Scalable models for high-dimensional neural data

https://scalablemodels.wordpress.com/2014/03

Scalable models for high-dimensional neural data. A COSYNE 2014 Workshop. Monthly Archives: March 2014. Scalable models workshop recap. March 8, 2014. This blog post is collaboratively written by Evan. The Scalable Models workshop was a remarkable success! Here we summarize each talk:. Konrad Körding Big datasets of spike data: why it is coming and why it is useful. Cybulski, T. R., Glaser, J. I., Marblestone, A. H., Zamft, B. M., Boyden, E. S., Church, G. M&#4...Neuroscience will need new software tools...

scalablemodels.wordpress.com scalablemodels.wordpress.com

Scalable models workshop recap | Scalable models for high-dimensional neural data

https://scalablemodels.wordpress.com/2014/03/08/scalable-models-workshop-summary-and-recap/comment-page-1

Scalable models for high-dimensional neural data. A COSYNE 2014 Workshop. Scalable models workshop recap. March 8, 2014. This blog post is collaboratively written by Evan. The Scalable Models workshop was a remarkable success! Here we summarize each talk:. Konrad Körding Big datasets of spike data: why it is coming and why it is useful. Cybulski, T. R., Glaser, J. I., Marblestone, A. H., Zamft, B. M., Boyden, E. S., Church, G. M., and Kording, K. P....Neuroscience will need new software tools to handle t...

scalablemodels.wordpress.com scalablemodels.wordpress.com

Scalable models workshop recap | Scalable models for high-dimensional neural data

https://scalablemodels.wordpress.com/2014/03/08/scalable-models-workshop-summary-and-recap

Scalable models for high-dimensional neural data. A COSYNE 2014 Workshop. Scalable models workshop recap. March 8, 2014. This blog post is collaboratively written by Evan. The Scalable Models workshop was a remarkable success! Here we summarize each talk:. Konrad Körding Big datasets of spike data: why it is coming and why it is useful. Cybulski, T. R., Glaser, J. I., Marblestone, A. H., Zamft, B. M., Boyden, E. S., Church, G. M., and Kording, K. P....Neuroscience will need new software tools to handle t...

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Evan Archer

Black-box variational state space models. Centered Dirichlet Mixture (CDM) Entropy Estimator. Pitman-Yor Mixture (PYM) Entropy Estimator. I’m Evan Archer, a researcher in the Department of Statistics. I work on research problems at the intersection of computational neuroscience, statistics, and machine learning. When I’m not pondering math and science I’m a big fan of travel, novels, running, and riding and building bicycles. First initial)(last name) at utexas dot edu.

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