MauroCE/Dissertation

Third year mathematics dissertation on variational, laplace and mcmc approximations of bayesian logistic regression

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mozzhorin/VIRGMo

Variational Inference for Random Graph Models

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wmkouw/nsi-emps

System identification on electro-mechanical positioning system via free energy minimization

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mkomod/variational-inference

Statistical Machine Learning Project on Variational Inference

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weichengv/BANNs

Code and Simulations using Biologically Annotated Neural Networks (BANNs)

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data-datum/deep_learning_onboarding

List of resources for deep learning

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clintlombard/stm-mapping

Stochastic Triangular Mesh (STM) Mapping — an online dense mapping technique for mobile robots.

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Develop-Packt/Topic-Modeling

You will evaluate latent Dirichlet allocation models and execute non-negative matrix factorization models. Finally, you will interpret the results of topic models and identify the best topic model for the given scenario. You will see how topic modelling provides insights into the underlying structure of documents. By the end of this course, you will be able to build fully functioning topic models to derive value and insights for your business

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zehsilva/poissonmf_cs

Code for "Content-Based Social Recommendation with Poisson Matrix Factorization" (ECML-PKDD 2017)

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singhalrk/Variational-Gradient-Matching

Variational Gradient Matching for Dynamical Systems

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AlexImmer/VIND

Variational Inference with Numerical Derivatives: variance reduction through coupling

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daandouwe/thesis

Neural language models with latent syntax.

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compops/ml-examples

Implementations from a graduate course following "Pattern Recognition and Machine Learning) written by Bishop and published in 2006.

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acabassi/vimix

R package for VIMIX: Variational Inference for MIXture models

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ldv1/bbvi_linear_models

Black-box variational inference, example for linear models

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robert-giaquinto/dapper

Fast implementation of DAP topic model using Conjugate Computation Variational Inference

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tlienart/thox

[done] phd thesis @ oxford stats

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gabrielnan/decoupled_gaussian_process Fork of google/decoupled_gaussian_process

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shuiruge/nn4post

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toologicbv/meta_learner

AI masterthesis. Iterative learning. Meta learning. Stochastic approach to adaptive computation

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kieranrcampbell/clvm

Variational inference for covariate latent variable models

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sunsided/CADL Fork of pkmital/CADL

Course/Homework materials for the "Creative Applications of Deep Learning with Tensorflow" MOOC

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