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Variational Inference

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TitleStatusHype
Approximate Bayesian inference in spatial environments—0
Approximate Decentralized Bayesian Inference—0
Approximate Inference by Compilation to Arithmetic Circuits—0
Approximate Inference for Spectral Mixture Kernel—0
Approximate Probabilistic Inference with Composed Flows—0
Approximating exponential family models (not single distributions) with a two-network architecture—0
Quantifying Variational Approximation for the Log-Partition Function—0
Approximation-Aware Bayesian Optimization—0
A Practical & Unified Notation for Information-Theoretic Quantities in ML—0
A Preference-oriented Diversity Model Based on Mutual-information in Re-ranking for E-commerce Search—0
Brain-like variational inference—0
A Primer on Variational Inference for Physics-Informed Deep Generative Modelling—0
A stable deep adversarial learning approach for geological facies generation—0
A Probabilistic Generative Model of Free Categories—0
A recursive Bayesian neural network for constitutive modeling of sands under monotonic loading—0
A Rigorous Link between Deep Ensembles and (Variational) Bayesian Methods—0
A Robust UCB Scheme for Active Learning in Regression from Strategic Crowds—0
A Rule for Gradient Estimator Selection, with an Application to Variational Inference—0
A Scalable Approach to Probabilistic Latent Space Inference of Large-Scale Networks—0
Score Operator Newton transport—0
A Semantically Consistent and Syntactically Variational Encoder-Decoder Framework for Paraphrase Generation—0
A Sparse and Adaptive Prior for Time-Dependent Model Parameters—0
A Sparsity-promoting Dictionary Model for Variational Autoencoders—0
Assessment of Uncertainty Quantification in Universal Differential Equations—0
A Statistically Principled and Computationally Efficient Approach to Speech Enhancement using Variational Autoencoders—0
Neural Latent Space Model for Dynamic Networks and Temporal Knowledge Graphs—0
A Stochastic approximation method for inference in probabilistic graphical models—0
A Stochastic Decoder for Neural Machine Translation—0
A Structured Variational Auto-encoder for Learning Deep Hierarchies of Sparse Features—0
Asynchronous Stochastic Variational Inference—0
A theoretical perspective on mode collapse in variational inference—0
Atmospheric Turbulence Correction via Variational Deep Diffusion—0
AtomAI: A Deep Learning Framework for Analysis of Image and Spectroscopy Data in (Scanning) Transmission Electron Microscopy and Beyond—0
A Trust-Region Method for Graphical Stein Variational Inference—0
A trust-region method for stochastic variational inference with applications to streaming data—0
Attention Is Not What You Need: Revisiting Multi-Instance Learning for Whole Slide Image Classification—0
A Tutorial on Deep Latent Variable Models of Natural Language—0
A Tutorial on Parametric Variational Inference—0
A Tutorial on Sparse Gaussian Processes and Variational Inference—0
A Tutorial on the Mathematical Model of Single Cell Variational Inference—0
A Unified Framework for Entropy Search and Expected Improvement in Bayesian Optimization—0
A universal probabilistic spike count model reveals ongoing modulation of neural variability—0
AUTM Flow: Atomic Unrestricted Time Machine for Monotonic Normalizing Flows—0
AutoBayes: A Compositional Framework for Generalized Variational Inference—0
Automated Variational Inference for Gaussian Process Models—0
Automated Variational Inference in Probabilistic Programming—0
Automatic Differentiation Variational Inference with Mixtures—0
Automatic Relevance Determination For Deep Generative Models—0
Automatic Variational ABC—0
Automatic Variational Inference in Stan—0
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