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Variational Inference

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TitleStatusHype
Interpretable Bayesian Tensor Network Kernel Machines with Automatic Rank and Feature SelectionCode0
Scalable Bayesian Low-Rank Adaptation of Large Language Models via Stochastic Variational Subspace InferenceCode0
VHU-Net: Variational Hadamard U-Net for Body MRI Bias Field Correction—0
Robust Recursive Fusion of Multiresolution Multispectral Images with Location-Aware Neural Networks—0
Variational Inference with Mixtures of Isotropic GaussiansCode0
Branching Stein Variational Gradient Descent for sampling multimodal distributions—0
Robust Filtering -- Novel Statistical Learning and Inference Algorithms with Applications—0
Bayesian Probabilistic Matrix Factorization—0
Variational Inference Optimized Using the Curved Geometry of Coupled Free Energy—0
Variational Supervised Contrastive Learning—0
Stability of Mean-Field Variational Inference—0
Rao-Blackwellised Reparameterisation Gradients—0
Bayesian Learning for Domain-Invariant Speaker Verification and Anti-Spoofing—0
Half-AVAE: Adversarial-Enhanced Factorized and Structured Encoder-Free VAE for Underdetermined Independent Component Analysis—0
Variational Inference for Quantum HyperNetworks—0
Semi-Implicit Variational Inference via Kernelized Path Gradient Descent—0
Amortized variational transdimensional inferenceCode0
MudiNet: Task-guided Disentangled Representation Learning for 5G Indoor Multipath-assisted Positioning—0
Variational Inference for Latent Variable Models in High Dimensions—0
Variational Adaptive Noise and Dropout towards Stable Recurrent Neural Networks—0
Self-supervised Latent Space Optimization with Nebula Variational Coding—0
Constrained Stein Variational Gradient Descent for Robot Perception, Planning, and Identification—0
Learning Distributions over Permutations and Rankings with Factorized Representations—0
Model Informed Flows for Bayesian Inference of Probabilistic Programs—0
Synonymous Variational Inference for Perceptual Image CompressionCode0
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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