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Variational Inference

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TitleStatusHype
Probabilistic Neural Transfer Function Estimation with Bayesian System Identification—0
Approximate Bayesian inference as a gauge theory—0
Empirical Bayes for Dynamic Bayesian Networks Using Generalized Variational Inference—0
Bayesian Neural Ordinary Differential Equations—0
Bayesian Neural Network via Stochastic Gradient Descent—0
A Forest Mixture Bound for Block-Free Parallel Inference—0
EinSteinVI: General and Integrated Stein Variational Inference—0
Disentangled Skill Embeddings for Reinforcement Learning—0
Bayesian Neural Networks with Domain Knowledge Priors—0
Elements of Sequential Monte Carlo—0
Embarrassingly Parallel Variational Inference in Nonconjugate Models—0
Disentangled Representation Learning with Transmitted Information Bottleneck—0
Disease Trajectory Maps—0
Nash: Neural Adaptive Shrinkage for Structured High-Dimensional Regression—0
Discrete-Valued Neural Networks Using Variational Inference—0
Disentangling by Partitioning: A Representation Learning Framework for Multimodal Sensory Data—0
Disentangling impact of capacity, objective, batchsize, estimators, and step-size on flow VI—0
A Particle Algorithm for Mean-Field Variational Inference—0
Disentangling Space and Time in Video with Hierarchical Variational Auto-encoders—0
Distributed Bayesian Estimation in Sensor Networks: Consensus on Marginal Densities—0
Distributed Bayesian Learning with Stochastic Natural-gradient Expectation Propagation and the Posterior Server—0
Distributed Multitask Reinforcement Learning with Quadratic Convergence—0
Large Skew-t Copula Models and Asymmetric Dependence in Intraday Equity Returns—0
EigenVI: score-based variational inference with orthogonal function expansions—0
Bayesian Neural Networks: A Min-Max Game Framework—0
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