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searching for Approximate inference 15 found (23 total)

Generalized linear mixed model (834 words) [view diff] case mismatch in snippet view article find links to article

generalized linear model Breslow, N. E.; Clayton, D. G. (1993), "Approximate Inference in Generalized Linear Mixed Models", Journal of the American Statistical

Jonathan Kuck (854 words) [view diff] case mismatch in snippet view article find links to article

Computer Science at Stanford University with a PhD Thesis titled, Fast Approximate Inference: Shifting the Pareto Frontier via Adaptation - advised by Stefano

Collective classification (2,333 words) [view diff] exact match in snippet view article find links to article

propagating information between nodes in the network to perform approximate inference. Approaches that use collective classification can make use of relational

Probabilistic logic programming (1,199 words) [view diff] no match in snippet view article find links to article

Probabilistic logic programming is a programming paradigm that combines logic programming with probabilities. Most approaches to probabilistic logic programming

Dynamic Bayesian network (709 words) [view diff] no match in snippet view article find links to article

license) libDAI: C++ library that provides implementations of various (approximate) inference methods for discrete graphical models; supports arbitrary factor

Markov logic network (1,077 words) [view diff] exact match in snippet view article find links to article

practice, the exact probability is often approximated. Techniques for approximate inference include Gibbs sampling, belief propagation, or approximation via

Nancy Reid (1,340 words) [view diff] exact match in snippet view article find links to article

the Guy medal in Gold "for her pioneering work on higher-order approximate inference which provides a foundational basis for optimal information extraction

Variational autoencoder (3,967 words) [view diff] case mismatch in snippet view article find links to article

Shakir; Wierstra, Daan (2014-06-18). "Stochastic Backpropagation and Approximate Inference in Deep Generative Models". International Conference on Machine

Generative adversarial network (13,881 words) [view diff] exact match in snippet view article find links to article

Already in the original paper, the authors noted that "Learned approximate inference can be performed by training an auxiliary network to predict z {\displaystyle

Boltzmann machine (3,676 words) [view diff] exact match in snippet view article find links to article

sufficient statistics by using Markov chain Monte Carlo (MCMC). This approximate inference, which must be done for each test input, is about 25 to 50 times

Support vector machine (9,068 words) [view diff] case mismatch in snippet view article find links to article

Wenzel; Matthäus Deutsch; Théo Galy-Fajou; Marius Kloft; ”Scalable Approximate Inference for the Bayesian Nonlinear Support Vector Machine” Ferris, Michael

Amnon Shashua (1,690 words) [view diff] exact match in snippet view article find links to article

algebraic systems in vision and learning, primal/dual optimization for approximate inference in MRF and Graphical models, and (since 2014) deep layered networks

Pfaffian (3,930 words) [view diff] exact match in snippet view article find links to article

arXiv:math/0406301. Globerson, Amir; Jaakkola, Tommi (2007). "Approximate inference using planar graph decomposition" (PDF). Advances in Neural Information

Information field theory (6,016 words) [view diff] no match in snippet view article find links to article

formalism the Gibbs free energy can be calculated, which permits the (approximate) inference of the posterior mean field via a numerical robust functional minimization

Multiple object tracking (7,676 words) [view diff] exact match in snippet view article find links to article

"Explaining human multiple object tracking as resource-constrained approximate inference in a dynamic probabilistic model". In Bengio, Y.; Schuurmans, D