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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
Variational Entropy Search for Adjusting Expected Improvement—0
Uncertainty Quantification of Graph Convolution Neural Network Models of Evolving Processes—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
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