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Variational Inference

1946 directly classified papers

Papers per year

Papers

Pathwise Derivatives Beyond the Reparameterization Trick ICML 2018
Learning From Noisy Web Data With Category-Level Supervision CVPR 2018
Variational Bayesian dropout: pitfalls and fixes ICML 2018
Inference Suboptimality in Variational Autoencoders ICML 2018
Variational Inference and Model Selection with Generalized Evidence Bounds ICML 2018
Quasi-Monte Carlo Variational Inference ICML 2018
Efficient Gradient-Free Variational Inference using Policy Search ICML 2018
oi-VAE: Output Interpretable VAEs for Nonlinear Group Factor Analysis ICML 2018
Hamiltonian Variational Auto-Encoder NIPS 2018
IntroVAE: Introspective Variational Autoencoders for Photographic Image Synthesis NIPS 2018
Explaining Deep Learning Models -- A Bayesian Non-parametric Approach NIPS 2018
Variational Autoencoders for Deforming 3D Mesh Models CVPR 2018
Generalized Zero-Shot Learning via Synthesized Examples CVPR 2018
Amortized Inference Regularization NIPS 2018
Variational Inference with Tail-adaptive f-Divergence NIPS 2018
Non-Adversarial Mapping with VAEs NIPS 2018
Deep Poisson gamma dynamical systems NIPS 2018
GILBO: One Metric to Measure Them All NIPS 2018
Unsupervised Image-to-Image Translation Using Domain-Specific Variational Information Bound NIPS 2018
MiME: Multilevel Medical Embedding of Electronic Health Records for Predictive Healthcare NIPS 2018
Modeling Facial Geometry Using Compositional VAEs CVPR 2018
Variational Sequential Labelers for Semi-Supervised Learning EMNLP 2018
Coherence-Aware Neural Topic Modeling EMNLP 2018
Can clustering scale sublinearly with its clusters? A variational EM acceleration of GMMs and k-means AISTATS 2018
On the challenges of learning with inference networks on sparse, high-dimensional data AISTATS 2018