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Variational Inference

1946 directly classified papers

Papers per year

Papers

Unconstrained Monotonic Neural Networks NIPS 2019
Explicit Disentanglement of Appearance and Perspective in Generative Models NIPS 2019
Implicit Generation and Modeling with Energy Based Models NIPS 2019
vGraph: A Generative Model for Joint Community Detection and Node Representation Learning NIPS 2019
A Prior of a Googol Gaussians: a Tensor Ring Induced Prior for Generative Models NIPS 2019
Explicitly disentangling image content from translation and rotation with spatial-VAE NIPS 2019
The Thermodynamic Variational Objective NIPS 2019
Variational Denoising Network: Toward Blind Noise Modeling and Removal NIPS 2019
Structured Variational Inference in Continuous Cox Process Models NIPS 2019
Neural Spline Flows NIPS 2019
Don't Blame the ELBO! A Linear VAE Perspective on Posterior Collapse NIPS 2019
Divide and Couple: Using Monte Carlo Variational Objectives for Posterior Approximation NIPS 2019
Adaptive Density Estimation for Generative Models NIPS 2019
ODE2VAE: Deep generative second order ODEs with Bayesian neural networks NIPS 2019
BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling NIPS 2019
Integer Discrete Flows and Lossless Compression NIPS 2019
Variational Graph Recurrent Neural Networks NIPS 2019
Provable Gradient Variance Guarantees for Black-Box Variational Inference NIPS 2019
Deep Random Splines for Point Process Intensity Estimation of Neural Population Data NIPS 2019
D-VAE: A Variational Autoencoder for Directed Acyclic Graphs NIPS 2019
Conditional Structure Generation through Graph Variational Generative Adversarial Nets NIPS 2019
Copula-like Variational Inference NIPS 2019
A Primal-Dual link between GANs and Autoencoders NIPS 2019
Semi-Implicit Graph Variational Auto-Encoders NIPS 2019
Improving Textual Network Learning with Variational Homophilic Embeddings NIPS 2019