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Variational Inference

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Showing 26–50 of 2274 papers

TitleStatusHype
Nearly Dimension-Independent Convergence of Mean-Field Black-Box Variational Inference—0
Variational Deep Learning via Implicit Regularization—0
Scalable Gaussian Processes with Low-Rank Deep Kernel Decomposition—0
Bayesian Meta-Reinforcement Learning with Laplace Variational Recurrent NetworksCode0
Efficient Training of Neural SDEs Using Stochastic Optimal Control—0
Exponential Convergence of CAVI for Bayesian PCA—0
Personalized Bayesian Federated Learning with Wasserstein Barycenter Aggregation—0
Training Latent Diffusion Models with Interacting Particle Algorithms—0
PhiNet v2: A Mask-Free Brain-Inspired Vision Foundation Model from VideoCode0
Nash: Neural Adaptive Shrinkage for Structured High-Dimensional Regression—0
FlowVAT: Normalizing Flow Variational Inference with Affine-Invariant Tempering—0
Combining Bayesian Inference and Reinforcement Learning for Agent Decision Making: A Review—0
Channel Fingerprint Construction for Massive MIMO: A Deep Conditional Generative Approach—0
Causal View of Time Series Imputation: Some Identification Results on Missing Mechanism—0
Stochastic Variational Propagation: Local, Scalable and Efficient Alternative to Backpropagation—0
Variational Formulation of the Particle Flow Particle Filter—0
IntrinsicTimescales.jl: A Julia package to estimate intrinsic (neural) timescales (INTs) from time-series data—0
Factor Analysis with Correlated Topic Model for Multi-Modal Data—0
Expected Free Energy-based Planning as Variational Inference—0
Uncertainty quantification of neural network models of evolving processes via Langevin sampling—0
Large Language Bayes—0
Uncertainty Estimation for Trust Attribution to Speed-of-Sound Reconstruction with Variational Networks—0
No-Regret Generative Modeling via Parabolic Monge-Ampère PDE—0
Unifying and extending Diffusion Models through PDEs for solving Inverse Problems—0
Variational Self-Supervised Learning—0
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