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Variational Inference

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TitleStatusHype
Distance-Preserving Spatial Representations in Genomic Data—0
Amortized Inference of Variational Bounds for Learning Noisy-OR—0
Spike-and-slab shrinkage priors for structurally sparse Bayesian neural networks—0
Continual Learning with Adaptive Weights (CLAW)—0
Automated Variational Inference in Probabilistic Programming—0
Automated Variational Inference for Gaussian Process Models—0
A Deterministic Global Optimization Method for Variational Inference—0
Constraint-Conditioned Policy Optimization for Versatile Safe Reinforcement Learning—0
Gaussian Variational State Estimation for Nonlinear State-Space Models—0
Amortized Context Vector Inference for Sequence-to-Sequence Networks—0
A Bayesian Detect to Track System for Robust Visual Object Tracking and Semi-Supervised Model Learning—0
Amortized Bayesian Meta-Learning—0
A Deep Variational Bayesian Framework for Blind Image Deblurring—0
Continuous Time Dynamic Topic Models—0
Convolutional Normalizing Flows for Deep Gaussian Processes—0
AutoBayes: A Compositional Framework for Generalized Variational Inference—0
AUTM Flow: Atomic Unrestricted Time Machine for Monotonic Normalizing Flows—0
Amortized backward variational inference in nonlinear state-space models—0
A universal probabilistic spike count model reveals ongoing modulation of neural variability—0
Amortised MAP Inference for Image Super-resolution—0
Constrained Bayesian Inference for Low Rank Multitask Learning—0
A Unified Framework for Entropy Search and Expected Improvement in Bayesian Optimization—0
Variational inference of fractional Brownian motion with linear computational complexity—0
Confidence Estimation via Sequential Likelihood Mixing—0
A Deep Learning Algorithm for High-Dimensional Exploratory Item Factor Analysis—0
A Tutorial on the Mathematical Model of Single Cell Variational Inference—0
Block-Term Tensor Decomposition Model Selection and Computation: The Bayesian Way—0
Connection Discovery using Shared Images by Gaussian Relational Topic Model—0
Constrained Stein Variational Gradient Descent for Robot Perception, Planning, and Identification—0
A Tutorial on Sparse Gaussian Processes and Variational Inference—0
A Tutorial on Parametric Variational Inference—0
A deep generative model for single-cell RNA sequencing with application to detecting differentially expressed genes—0
A Tutorial on Deep Latent Variable Models of Natural Language—0
Attention Is Not What You Need: Revisiting Multi-Instance Learning for Whole Slide Image Classification—0
A Mathematical Walkthrough and Discussion of the Free Energy Principle—0
Alpha-VI DeepONet: A prior-robust variational Bayesian approach for enhancing DeepONets with uncertainty quantification—0
A trust-region method for stochastic variational inference with applications to streaming data—0
A Trust-Region Method for Graphical Stein Variational Inference—0
-VAEs : Optimising variational inference by learning data-dependent divergence skew—0
AtomAI: A Deep Learning Framework for Analysis of Image and Spectroscopy Data in (Scanning) Transmission Electron Microscopy and Beyond—0
Atmospheric Turbulence Correction via Variational Deep Diffusion—0
Alpha-divergence Variational Inference Meets Importance Weighted Auto-Encoders: Methodology and Asymptotics—0
A Closer Look at Disentangling in β-VAE—0
Constrained Structure Learning for Scene Graph Generation—0
A theoretical perspective on mode collapse in variational inference—0
Alpha-Divergences in Variational Dropout—0
A Deeper Look at the Unsupervised Learning of Disentangled Representations in β-VAE from the Perspective of Core Object Recognition—0
Computing with Categories in Machine Learning—0
Concurrent Training and Layer Pruning of Deep Neural Networks—0
Alpha-Beta Divergence For Variational Inference—0
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