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Variational Inference

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Showing 501–550 of 2274 papers

TitleStatusHype
Linear Time GPs for Inferring Latent Trajectories from Neural Spike Trains—0
On the Convergence of Coordinate Ascent Variational Inference—0
Balanced Training of Energy-Based Models with Adaptive Flow Sampling—0
Learning to solve Bayesian inverse problems: An amortized variational inference approach using Gaussian and Flow guidesCode0
Neural Markov Jump ProcessesCode0
Low-rank extended Kalman filtering for online learning of neural networks from streaming dataCode1
Scalable Learning of Latent Language Structure With Logical Offline Cycle Consistency—0
Learning a Structural Causal Model for Intuition Reasoning in ConversationCode1
Federated Empirical Risk Minimization via Second-Order Method—0
Provably Fast Finite Particle Variants of SVGD via Virtual Particle Stochastic Approximation—0
Differentiable Random Partition ModelsCode0
On the Convergence of Black-Box Variational Inference—0
A Rigorous Link between Deep Ensembles and (Variational) Bayesian Methods—0
Discriminative calibration: Check Bayesian computation from simulations and flexible classifierCode0
Tuning-Free Maximum Likelihood Training of Latent Variable Models via Coin Betting—0
Bayesian calibration of differentiable agent-based models—0
Deep Functional Factor Models: Forecasting High-Dimensional Functional Time Series via Bayesian Nonparametric FactorizationCode0
DIVA: A Dirichlet Process Mixtures Based Incremental Deep Clustering Algorithm via Variational Auto-EncoderCode1
Federated Variational Inference: Towards Improved Personalization and Generalization—0
Towards Understanding the Dynamics of Gaussian-Stein Variational Gradient Descent—0
Variational Inference with Coverage Guarantees in Simulation-Based InferenceCode0
Confidence-aware Personalized Federated Learning via Variational Expectation MaximizationCode1
Seismic Random Noise Attenuation Based on Non-IID Pixel-Wise Gaussian Noise ModelingCode0
Score Operator Newton transport—0
Refining Amortized Posterior Approximations using Gradient-Based Summary Statistics—0
A stable deep adversarial learning approach for geological facies generation—0
Fully Bayesian VIB-DeepSSMCode0
FedHB: Hierarchical Bayesian Federated Learning—0
Atmospheric Turbulence Correction via Variational Deep Diffusion—0
Variational Nonlinear Kalman Filtering with Unknown Process Noise Covariance—0
Towards Causal Representation Learning and Deconfounding from Indefinite Data—0
Tensorizing flows: a tool for variational inference—0
Variational Inference for Bayesian Neural Networks under Model and Parameter UncertaintyCode0
Causal Semantic Communication for Digital Twins: A Generalizable Imitation Learning Approach—0
Score-Based Diffusion Models as Principled Priors for Inverse ImagingCode1
Machine Learning and the Future of Bayesian Computation—0
Likelihood-Based Generative Radiance Field with Latent Space Energy-Based Model for 3D-Aware Disentangled Image Representation—0
The Deep Latent Position Topic Model for Clustering and Representation of Networks with Textual Edges—0
Bayesian Inference on Brain-Computer Interfaces via GLASSCode0
Black Box Variational Inference with a Deterministic Objective: Faster, More Accurate, and Even More Black BoxCode0
Forward-backward Gaussian variational inference via JKO in the Bures-Wasserstein Space—0
Bayesian neural networks via MCMC: a Python-based tutorialCode1
The Wyner Variational Autoencoder for Unsupervised Multi-Layer Wireless Fingerprinting—0
Variational Distribution Learning for Unsupervised Text-to-Image Generation—0
Efficient Alternating Minimization Solvers for Wyner Multi-View Unsupervised LearningCode0
Variational Inference for Longitudinal Data Using Normalizing FlowsCode0
Convergence Analysis of Stochastic Gradient Descent with MCMC Estimators—0
Dynamical Hyperspectral Unmixing with Variational Recurrent Neural NetworksCode0
Practical and Matching Gradient Variance Bounds for Black-Box Variational Bayesian Inference—0
Hybrid Variational Autoencoder for Time Series Forecasting—0
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