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⚙️AlgorithmAdvanced

Wake-Sleep Algorithm

The Wake–Sleep algorithm trains a pair of models: a generative model that explains how data are produced and a recognition model that guesses hidden causes from observed data.

#wake-sleep#helmholtz machine#generative model+12
📚TheoryAdvanced

Variational Dropout & Bayesian Deep Learning

Dropout can be interpreted as variational inference in a Bayesian neural network, where applying random masks approximates sampling from a posterior over weights.

#bayesian neural networks
Advanced
Filtering by:
#variational inference
#variational inference
#dropout
+12
📚TheoryAdvanced

Normalizing Flow Variational Inference

Normalizing-flow variational inference enriches the variational family by transforming a simple base distribution through a sequence of invertible, differentiable mappings.

#normalizing flows#variational inference#elbo+12
⚙️AlgorithmAdvanced

Stochastic Variational Inference

Stochastic Variational Inference (SVI) scales variational inference to large datasets by taking noisy but unbiased gradient steps using minibatches.

#stochastic variational inference#elbo#variational inference+12
∑MathAdvanced

Evidence Lower Bound (ELBO)

The Evidence Lower Bound (ELBO) is a tractable lower bound on the log evidence log p(x) used to perform approximate Bayesian inference.

#elbo#variational inference#vae+12
📚TheoryAdvanced

Disentangled Representations

Disentangled representations aim to encode independent factors of variation (like shape, size, or color) into separate coordinates of a latent vector.

#disentangled representations#independent factors#total correlation+12
⚙️AlgorithmAdvanced

Natural Gradient Method

Natural gradient scales the ordinary gradient by the inverse Fisher information matrix to account for the geometry of probability distributions.

#natural gradient#fisher information#empirical fisher+12
📚TheoryAdvanced

Variational Inference Theory

Variational Inference (VI) replaces an intractable posterior with a simpler distribution and optimizes it by minimizing KL divergence, which is equivalent to maximizing the ELBO.

#variational inference#elbo#kl divergence+12