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 blog.shakirm.com
A Year of Approximate Inference: Review of the NIPS 2015 Workshop - The Spectator
| | resources.paperdigest.org
Paper Digest: NIPS 2018 Highlights - Resources | Paper Digest
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| | Download NIPS-2018-Paper-Digests.pdf- highlights of all NIPS-2018 papers. The Conference on Neural Information Processing Systems (NIPS) is one of the top machine learning conferences in the world. In 2018, it is to be held in Montreal, Canada. There were ~4,800 paper submissions, of which 1009
| | vxlabs.com
Variational Autoencoder in PyTorch, commented and annotated. - vxlabs
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| | I have recently become fascinated with (Variational) Autoencoders and with PyTorch. Kevin Frans has a beautiful blog post online explaining variational autoencoders, with examples in TensorFlow and, importantly, with cat pictures. Jaan Altosaar's blog post takes an even deeper look at VAEs from both the deep learning perspective and the perspective of graphical models. Both of these posts, as well as Diederik Kingma's original 2014 paper Auto-Encoding Variational Bayes, are more than worth your time.
| | darrenjw.wordpress.com
Introduction to Approximate Bayesian Computation (ABC) - i am become computational
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| | Reblogged on WordPress.com
| | qbnets.wordpress.com
My Identifiability Checker Works! Verified Judea Pearl's Backdoor and Frontdoor adjustment formulae | Quantum Bayesian Networks
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| My software is working! I am ecstatic. In a previous blog post entitled "Simple, Monte Carlo driven, Pearl-identifiability checker" which I wrote 2 days ago, I described my future plans to add to my software JudeasRx, an "identifiability checker" based on a very efficient and mature MCMC (Markov Chain Monte Carlo) Python software library called...