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Variational Inference

Papers

Showing 701750 of 2274 papers

TitleStatusHype
Additive Multi-Index Gaussian process modeling, with application to multi-physics surrogate modeling of the quark-gluon plasma0
VIFS: An End-to-End Variational Inference for Foley Sound SynthesisCode0
Improving Hyperparameter Learning under Approximate Inference in Gaussian Process ModelsCode0
GCD-DDPM: A Generative Change Detection Model Based on Difference-Feature Guided DDPMCode0
Input-gradient space particle inference for neural network ensemblesCode0
Deep Active Learning with Structured Neural Depth Search0
Provable convergence guarantees for black-box variational inference0
Variational Gaussian Process Diffusion ProcessesCode0
Linear Time GPs for Inferring Latent Trajectories from Neural Spike Trains0
On the Convergence of Coordinate Ascent Variational Inference0
Balanced Training of Energy-Based Models with Adaptive Flow Sampling0
Learning to solve Bayesian inverse problems: An amortized variational inference approach using Gaussian and Flow guidesCode0
Neural Markov Jump ProcessesCode0
Scalable Learning of Latent Language Structure With Logical Offline Cycle Consistency0
Federated Empirical Risk Minimization via Second-Order Method0
Provably Fast Finite Particle Variants of SVGD via Virtual Particle Stochastic Approximation0
Differentiable Random Partition ModelsCode0
Tuning-Free Maximum Likelihood Training of Latent Variable Models via Coin Betting0
A Rigorous Link between Deep Ensembles and (Variational) Bayesian Methods0
Discriminative calibration: Check Bayesian computation from simulations and flexible classifierCode0
On the Convergence of Black-Box Variational Inference0
Bayesian calibration of differentiable agent-based models0
Variational Inference with Coverage Guarantees in Simulation-Based InferenceCode0
Federated Variational Inference: Towards Improved Personalization and Generalization0
Towards Understanding the Dynamics of Gaussian-Stein Variational Gradient Descent0
Deep Functional Factor Models: Forecasting High-Dimensional Functional Time Series via Bayesian Nonparametric FactorizationCode0
Score Operator Newton transport0
Seismic Random Noise Attenuation Based on Non-IID Pixel-Wise Gaussian Noise ModelingCode0
Refining Amortized Posterior Approximations using Gradient-Based Summary Statistics0
A stable deep adversarial learning approach for geological facies generation0
Fully Bayesian VIB-DeepSSMCode0
FedHB: Hierarchical Bayesian Federated Learning0
Atmospheric Turbulence Correction via Variational Deep Diffusion0
Variational Nonlinear Kalman Filtering with Unknown Process Noise Covariance0
Towards Causal Representation Learning and Deconfounding from Indefinite Data0
Tensorizing flows: a tool for variational inference0
Variational Inference for Bayesian Neural Networks under Model and Parameter UncertaintyCode0
Causal Semantic Communication for Digital Twins: A Generalizable Imitation Learning Approach0
Machine Learning and the Future of Bayesian Computation0
Likelihood-Based Generative Radiance Field with Latent Space Energy-Based Model for 3D-Aware Disentangled Image Representation0
The Deep Latent Position Topic Model for Clustering and Representation of Networks with Textual Edges0
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 Space0
Variational Distribution Learning for Unsupervised Text-to-Image Generation0
The Wyner Variational Autoencoder for Unsupervised Multi-Layer Wireless Fingerprinting0
Efficient Alternating Minimization Solvers for Wyner Multi-View Unsupervised LearningCode0
Variational Inference for Longitudinal Data Using Normalizing FlowsCode0
Dynamical Hyperspectral Unmixing with Variational Recurrent Neural NetworksCode0
Convergence Analysis of Stochastic Gradient Descent with MCMC Estimators0
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