probabilistic-numerics.org
Probabilistic Numerics.org
http://www.probabilistic-numerics.org/2014/09/01/Roundtable-ProbNum-ProbProg
For list of all posts). Jan 16, 2015. Connections, Part III: Bayesian Optimization. Jan 15, 2015. Connections, Part II: Stochastic numerical methods. Jan 14, 2015. Connections, Part I: Uncertainty Quantification. Sep 5, 2014. Sep 3, 2014. Tübingen Manifesto: Priors and Prior Work. Sep 1, 2014. Tübingen Manifesto: Probabilistic Numerics and Probabilistic Programming. Aug 27, 2014. Aug 22, 2014. Tübingen Manifesto: Probabilistic Numerics and Probabilistic Programming. By Michael A Osborne,. ProbProg seems ...
probabilistic-numerics.org
Probabilistic Numerics.org
http://www.probabilistic-numerics.org/2014/09/05/Roundtable-Community
For list of all posts). Jan 16, 2015. Connections, Part III: Bayesian Optimization. Jan 15, 2015. Connections, Part II: Stochastic numerical methods. Jan 14, 2015. Connections, Part I: Uncertainty Quantification. Sep 5, 2014. Sep 3, 2014. Tübingen Manifesto: Priors and Prior Work. Sep 1, 2014. Tübingen Manifesto: Probabilistic Numerics and Probabilistic Programming. Aug 27, 2014. Aug 22, 2014. By Michael A Osborne,. Who Are Our Users? Before we can address some of the questions considered in the last post.
projects.csail.mit.edu
Church Wiki
http://projects.csail.mit.edu/church/wiki/Church
Church is a probabilistic programming language. Designed for expressive description of generative models (Goodman, Mansinghka, Roy, Bonawitz and Tenenbaum, 2008). Church is a derivative of the programming language Scheme. With probabilistic semantics. This website serves as a portal to work related to Church, tutorials, reference implementations and a repository of probabilistic models expressed in Church. Probabilistic Models of Cognition. Older tutorials: Old PMC Tutorial. Many probabilistic models are...
machinedlearnings.com
Machined Learnings: December 2013
http://www.machinedlearnings.com/2013_12_01_archive.html
Cue Butlerian Jihad in 3, 2, 1, . Thursday, December 12, 2013. Was fabulous this year, kudos to all the organizers, area chairs, reviewers, and volunteers. Between the record number of attendees, multitude of corporate sponsors, and the Mark Zuckerburg show. This year's conference is most notable for sheer magnitude. It's past the point that one person can summarize it effectively, but here's my retrospective, naturally heavily biased towards my interests. Platform will be around courtship techniques.
cocosci.mit.edu
MIT Computational Cognitive Science Group - People
http://cocosci.mit.edu/people
MIT Computational Cognitive Science Group. Department of Brain and Cognitive Sciences, MIT. In my research, I develop mathematical models of the way children learn language and the way adults generalize linguistic rules to create new words and sentences. My research draws on experimental methods from psychology, formal modeling techniques from natural language processing, theoretical tools from linguistics, and problems from all three. I am interested in these basic questions, working on modeling both in...
szamitogepesnyelveszet.blogspot.com
NLP Meetup - Számítógépes Nyelvészet: március 2013
http://szamitogepesnyelveszet.blogspot.com/2013_03_01_archive.html
NLP Meetup - Számítógépes Nyelvészet. Számítógépes nyelvészet és egyéb formális nyalánkságok. Posted by Zoltán Varjú. Az utóbbi napokban a Twitter a DARPA Probabilistic Programming for Advanced Machine Learning (PPAML) Proposers' Day. Től hangos. De miért? Rob Zinkov Why Probabilistic Programming Matters. Posztjában így válaszolja meg a kérdést. Aki bele szeretne csapni a lecsóba, annak a Church. Nyelvet ajánlom (ami a Scheme család tagja). A Probabilistic Models of Cognition. Haskeller-ek a haskell....
blog.opencog.org
Why Hypergraphs? | OpenCog Brainwave
http://blog.opencog.org/2013/03/24/why-hypergraphs
The latest developments in building an open-source mind. Catalog of Current OpenCog Atom Types. The Relationship Between PLN Inference and Gibbs Sampling (Some Thought-Experiments) →. March 24, 2013. To represent knowledge. Why? I don’t think this is clearly, succinctly explained anywhere, so I will try to do so here. This is a very important point: I can’t begin to tell you how many times I went searching. Or some probabilistic programming system. Looks like a graph with two vertexes,. So you’d th...
moalquraishi.wordpress.com
The State of Probabilistic Programming « Some Thoughts on a Mysterious Universe
https://moalquraishi.wordpress.com/2015/03/29/the-state-of-probabilistic-programming
Some Thoughts on a Mysterious Universe. The State of Probabilistic Programming. March 29, 2015. For two weeks last July, I cocooned myself in a hotel in Portland, OR, living and breathing probabilistic programming as a student in the probabilistic programming summer school. The school is part of the broader DARPA program on Probabilistic Programming for Advanced Machine Learning (PPAML). Which did a terrific job of organizing the event. Thankfully, they’re hosting the summer school again this year. Befor...
dk-techlogic.blogspot.com
TECH LOGIC: Machine Learning Resources for Beginners and Beginners++
http://dk-techlogic.blogspot.com/2012/05/best-machine-learning-resources.html
Machine Learning Resources for Beginners and Beginners. I have been learning ML for sometime now and I have spent some time on finding what are some of the good resources for ML. For Beginners. Compiling mex files on 64bit Linux(UBUNTU) using MATLAB 2012. I could not setup the compiler for myself to create mex files. So I searched the internet, going through many blogs and posts. Finally I go. Unsupervised Feature Learning and Deep Learning Resources. Setting up Theano on Ubuntu 14.04. Before starting I...
