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Variational Inference

373 papers with code · Reasoning

Fitting approximate posteriors with variational inference transforms the inference problem into an optimization problem, where the goal is (typically) to optimize the evidence lower bound (ELBO) on the log likelihood of the data.

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Greatest papers with code

Neural Variational Inference and Learning in Belief Networks

31 Jan 2014tensorflow/models

Highly expressive directed latent variable models, such as sigmoid belief networks, are difficult to train on large datasets because exact inference in them is intractable and none of the approximate inference methods that have been applied to them scale well.

LATENT VARIABLE MODELS VARIATIONAL INFERENCE

NeuTra-lizing Bad Geometry in Hamiltonian Monte Carlo Using Neural Transport

9 Mar 2019google-research/google-research

Hamiltonian Monte Carlo is a powerful algorithm for sampling from difficult-to-normalize posterior distributions.

VARIATIONAL INFERENCE

Adversarial Autoencoders

18 Nov 2015eriklindernoren/PyTorch-GAN

In this paper, we propose the "adversarial autoencoder" (AAE), which is a probabilistic autoencoder that uses the recently proposed generative adversarial networks (GAN) to perform variational inference by matching the aggregated posterior of the hidden code vector of the autoencoder with an arbitrary prior distribution.

CLUSTERING DATA VISUALIZATION DIMENSIONALITY REDUCTION UNSUPERVISED IMAGE CLASSIFICATION UNSUPERVISED MNIST VARIATIONAL INFERENCE

Doubly Stochastic Variational Inference for Deep Gaussian Processes

NeurIPS 2017 pyro-ppl/pyro

Existing approaches to inference in DGP models assume approximate posteriors that force independence between the layers, and do not work well in practice.

GAUSSIAN PROCESSES VARIATIONAL INFERENCE

Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm

NeurIPS 2016 pyro-ppl/pyro

We propose a general purpose variational inference algorithm that forms a natural counterpart of gradient descent for optimization.

BAYESIAN INFERENCE VARIATIONAL INFERENCE

Pyro: Deep Universal Probabilistic Programming

18 Oct 2018uber/pyro

Pyro is a probabilistic programming language built on Python as a platform for developing advanced probabilistic models in AI research.

PROBABILISTIC PROGRAMMING VARIATIONAL INFERENCE

Multi-Object Representation Learning with Iterative Variational Inference

1 Mar 2019deepmind/deepmind-research

Human perception is structured around objects which form the basis for our higher-level cognition and impressive systematic generalization abilities.

REPRESENTATION LEARNING SYSTEMATIC GENERALIZATION VARIATIONAL INFERENCE

Gaussian Processes for Big Data

26 Sep 2013cornellius-gp/gpytorch

We introduce stochastic variational inference for Gaussian process models.

GAUSSIAN PROCESSES LATENT VARIABLE MODELS VARIATIONAL INFERENCE

Auto-Encoding Variational Bayes

20 Dec 2013pytorch/botorch

First, we show that a reparameterization of the variational lower bound yields a lower bound estimator that can be straightforwardly optimized using standard stochastic gradient methods.

IMAGE CLUSTERING VARIATIONAL INFERENCE

GPflow: A Gaussian process library using TensorFlow

27 Oct 2016GPflow/GPflow

GPflow is a Gaussian process library that uses TensorFlow for its core computations and Python for its front end.

GAUSSIAN PROCESSES VARIATIONAL INFERENCE