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Variational Inference

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TitleStatusHype
Excess risk analysis for epistemic uncertainty with application to variational inference—0
BayesFormer: Transformer with Uncertainty Estimation—0
Amortized backward variational inference in nonlinear state-space models—0
Easy Variational Inference for Categorical Models via an Independent Binary ApproximationCode0
Variational inference via Wasserstein gradient flowsCode1
Efficient Transformed Gaussian Processes for Non-Stationary Dependent Multi-class Classification—0
Radial Spike and Slab Bayesian Neural Networks for Sparse Data in Ransomware Attacks—0
Rethinking Bayesian Learning for Data Analysis: The Art of Prior and Inference in Sparsity-Aware Modeling—0
Amortized Inference for Causal Structure LearningCode1
Single-cell gene regulatory network analysis for mixed cell populations with applications to COVID-19 single cell dataCode0
Flow-based Recurrent Belief State Learning for POMDPs—0
Quasi Black-Box Variational Inference with Natural Gradients for Bayesian Learning—0
RL with KL penalties is better viewed as Bayesian inference—0
Foundation Posteriors for Approximate Probabilistic Inference—0
Variational Inference for Bayesian Bridge Regression—0
Markov Chain Monte Carlo for Continuous-Time Switching Dynamical Systems—0
Taming Continuous Posteriors for Latent Variational Dialogue Policies—0
Fat-Tailed Variational Inference with Anisotropic Tail Adaptive Flows—0
MixFlows: principled variational inference via mixed flowsCode0
Importance Weighted Structure Learning for Scene Graph Generation—0
Exploiting Variational Domain-Invariant User Embedding for Partially Overlapped Cross Domain Recommendation—0
Generalized Variational Inference in Function Spaces: Gaussian Measures meet Bayesian Deep LearningCode0
Scalable Stochastic Parametric Verification with Stochastic Variational Smoothed Model Checking—0
Variational Inference MPC using Normalizing Flows and Out-of-Distribution Projection—0
Reducing Catastrophic Forgetting in Neural Networks via Gaussian Mixture Approximation—0
Robust Learning of Parsimonious Deep Neural Networks—0
A Probabilistic Generative Model of Free Categories—0
ReCAB-VAE: Gumbel-Softmax Variational Inference Based on Analytic Divergence—0
Variational Sparse Coding with Learned ThresholdingCode1
Optimal Lighting Control in Greenhouses Using Bayesian Neural Networks for Sunlight Prediction—0
Probabilistic Control and Majorization of Optimal Control—0
A Bayesian Detect to Track System for Robust Visual Object Tracking and Semi-Supervised Model Learning—0
VICE: Variational Interpretable Concept EmbeddingsCode1
Cluster-based Regression using Variational Inference and Applications in Financial Forecasting—0
Streaming Inference for Infinite Non-Stationary Clustering—0
Variational Kalman Filtering with Hinf-Based Correction for Robust Bayesian Learning in High Dimensions—0
Blind Equalization and Channel Estimation in Coherent Optical Communications Using Variational AutoencodersCode1
Learn from Unpaired Data for Image Restoration: A Variational Bayes ApproachCode1
An Energy-Based Prior for Generative SaliencyCode1
A Variational Approach to Bayesian Phylogenetic InferenceCode0
Conditional Injective Flows for Bayesian ImagingCode0
A Personalized Dialogue Generator with Implicit User Persona Detection—0
Gaussian Processes for Missing Value ImputationCode1
Diverse Text Generation via Variational Encoder-Decoder Models with Gaussian Process PriorsCode1
Discretely Indexed FlowsCode0
Provable concept learning for interpretable predictions using variational autoencodersCode1
Quantum-Aided Meta-Learning for Bayesian Binary Neural Networks via Born Machines—0
A Framework for Improving the Reliability of Black-box Variational InferenceCode1
Treatment Learning Causal Transformer for Noisy Image Classification—0
A Sparsity-promoting Dictionary Model for Variational Autoencoders—0
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