Explore >> Select a destination

You are here

 proceedings.neurips.cc
Hierarchical Implicit Models and Likelihood-Free Variational Inference
| | dustintran.com
Deep and Hierarchical Implicit Models | Dustin Tran
4.5 parsecs away

Travel
| | I'm excited to announce a paper that Rajesh Ranganath, Dave Blei, and I released today on arXiv, titled Deep and Hierarchical Implicit Models. Implicit probabilistic models are all about sampling as a primitive: they define a process to simulate data and do not require tractable densities (Diggle & Gratton (1984), Hartig, Calabrese, Reineking, Wiegand, & Huth (2011)) . We leverage this fundamental idea to develop new classes of models: they encompass simulators in the scientific communities, generative a...
| | www.depthfirstlearning.com
Variational Inference with Normalizing Flows ยท Depth First Learning
21.2 parsecs away

Travel
| |
| | nicholas.carlini.com
Adversarial Machine Learning Reading List
15.9 parsecs away

Travel
| | Abstract: This reading list provides an introduction to the field of adversarial examples for machine learning models.
| | 360digitmg.com
MLJAR AutoML - Features and Use Causes
95.8 parsecs away

Travel
| This article explains What is Machine learning has become a critical tool for businesses and organizations across industries.