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Variational Inference

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TitleStatusHype
Unveiling Implicit Deceptive Patterns in Multi-Modal Fake News via Neuro-Symbolic ReasoningCode1
Fast and Unified Path Gradient Estimators for Normalizing Flows—0
Federated Bayesian Deep Learning: The Application of Statistical Aggregation Methods to Bayesian Models—0
Variational Inference for Uncertainty Quantification: an Analysis of Trade-offsCode0
Neural Markov Random Field for Stereo MatchingCode2
Sequential Monte Carlo for Inclusive KL Minimization in Amortized Variational InferenceCode0
VISA: Variational Inference with Sequential Sample-Average Approximations—0
Nonparametric Automatic Differentiation Variational Inference with Spline Approximation—0
Variational Inference of Parameters in Opinion Dynamics Models—0
eXponential FAmily Dynamical Systems (XFADS): Large-scale nonlinear Gaussian state-space modelingCode1
An Efficient Difference-of-Convex Solver for Privacy FunnelCode0
Re-Envisioning Numerical Information Field Theory (NIFTy.re): A Library for Gaussian Processes and Variational Inference—0
Stable Training of Normalizing Flows for High-dimensional Variational InferenceCode0
Language-guided Skill Learning with Temporal Variational Inference—0
Accelerating Convergence of Stein Variational Gradient Descent via Deep UnfoldingCode0
A Framework for Variational Inference of Lightweight Bayesian Neural Networks with Heteroscedastic Uncertainties—0
Batch and match: black-box variational inference with a score-based divergenceCode2
Bayesian Neural Networks with Domain Knowledge Priors—0
Uncertainty Quantification of Graph Convolution Neural Network Models of Evolving Processes—0
Variational Entropy Search for Adjusting Expected Improvement—0
Training Bayesian Neural Networks with Sparse Subspace Variational InferenceCode0
BlackJAX: Composable Bayesian inference in JAXCode5
MCMC-driven learning—0
Variational Continual Test-Time Adaptation—0
Are Uncertainty Quantification Capabilities of Evidential Deep Learning a Mirage?Code0
Latent variable model for high-dimensional point process with structured missingnessCode0
The VampPrior Mixture ModelCode0
Variational Flow Models: Flowing in Your StyleCode0
Variational DAG Estimation via State Augmentation With Stochastic Permutations—0
A Differentiable Partially Observable Generalized Linear Model with Forward-Backward Message Passing—0
Self-Attention through Kernel-Eigen Pair Sparse Variational Gaussian ProcessesCode1
Bayesian Deep Learning for Remaining Useful Life Estimation via Stein Variational Gradient DescentCode1
Activity Detection for Massive Connectivity in Cell-free Networks with Unknown Large-scale Fading, Channel Statistics, Noise Variance, and Activity Probability: A Bayesian ApproachCode0
Multilayer Simplex-structured Matrix Factorization for Hyperspectral Unmixing with Endmember Variability—0
Towards Improved Variational Inference for Deep Bayesian Models—0
Efficient and Generalized end-to-end Autonomous Driving System with Latent Deep Reinforcement Learning and Demonstrations—0
Provably Scalable Black-Box Variational Inference with Structured Variational Families—0
Efficient Nonparametric Tensor Decomposition for Binary and Count DataCode0
Scalable and Efficient Methods for Uncertainty Estimation and Reduction in Deep Learning—0
DualVAE: Dual Disentangled Variational AutoEncoder for RecommendationCode0
VI-PANN: Harnessing Transfer Learning and Uncertainty-Aware Variational Inference for Improved Generalization in Audio Pattern RecognitionCode0
Text-Video Retrieval via Variational Multi-Modal Hypergraph Networks—0
Complementary Information Mutual Learning for Multimodality Medical Image Segmentation—0
Denoising Diffusion Variational Inference: Diffusion Models as Expressive Variational PosteriorsCode0
Unsupervised Outlier Detection using Random Subspace and Subsampling Ensembles of Dirichlet Process MixturesCode0
A Compact Representation for Bayesian Neural Networks By Removing Permutation SymmetryCode0
Continual Learning via Sequential Function-Space Variational InferenceCode1
Tractable Function-Space Variational Inference in Bayesian Neural NetworksCode0
GAD-PVI: A General Accelerated Dynamic-Weight Particle-Based Variational Inference Framework—0
Adaptive Message Passing: A General Framework to Mitigate Oversmoothing, Oversquashing, and UnderreachingCode1
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