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variational inference

2069 papers

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Also known as

VI-NET VRNN VBI SVI VIBE VQ-VAE ADVI VARNET MCVI PARVI SAVI VI VAE VMP VB BBVI ELBO VIB

Co-occurring keywords

bayesian inference (1904) gaussian process (1198) generative model (2889) variational autoencoder (1282) latent variable model (564) probabilistic modeling (851) representation learning (6174) uncertainty quantification (1365) latent variable (541) approximate inference (253)

Papers

Independent Subspace Analysis for Unsupervised Learning of Disentangled Representations AISTATS 2020
Neural Topic Model with Attention for Supervised Learning AISTATS 2020
Interpretable Deep Gaussian Processes with Moments AISTATS 2020
A Graph Auto-Encoder for Haplotype Assembly and Viral Quasispecies Reconstruction AAAI 2020
Infomax Neural Joint Source-Channel Coding via Adversarial Bit Flip AAAI 2020
Meta-Amortized Variational Inference and Learning AAAI 2020
Tree-Structured Neural Topic Model ACL 2020
Autoencoding Pixies: Amortised Variational Inference with Graph Convolutions for Functional Distributional Semantics ACL 2020
Neural Mixed Counting Models for Dispersed Topic Discovery ACL 2020
Effective Estimation of Deep Generative Language Models ACL 2020
Generating Diverse Translation from Model Distribution with Dropout EMNLP 2020
AIN: Fast and Accurate Sequence Labeling with Approximate Inference Network EMNLP 2020
VCDM: Leveraging Variational Bi-encoding and Deep Contextualized Word Representations for Improved Definition Modeling EMNLP 2020
Narrative Text Generation with a Latent Discrete Plan EMNLP 2020
Learning Informative Representations of Biomedical Relations with Latent Variable Models EMNLP 2020
Variational-EM-Based Deep Learning for Noise-Blind Image Deblurring CVPR 2020
Variational Context-Deformable ConvNets for Indoor Scene Parsing CVPR 2020
SVGD as a kernelized Wasserstein gradient flow of the chi-squared divergence NIPS 2020
A Non-Asymptotic Analysis for Stein Variational Gradient Descent NIPS 2020
Decision-Making with Auto-Encoding Variational Bayes NIPS 2020
Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows NIPS 2020
Beyond the Mean-Field: Structured Deep Gaussian Processes Improve the Predictive Uncertainties NIPS 2020
Learning Discrete Energy-based Models via Auxiliary-variable Local Exploration NIPS 2020
Efficient Marginalization of Discrete and Structured Latent Variables via Sparsity NIPS 2020
Invertible Gaussian Reparameterization: Revisiting the Gumbel-Softmax NIPS 2020