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Variational Inference

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TitleStatusHype
Elements of Sequential Monte Carlo—0
β-CapsNet: Learning Disentangled Representation for CapsNet by Information Bottleneck—0
A Generative Parser with a Discriminative Recognition Algorithm—0
Embarrassingly Parallel Variational Inference in Nonconjugate Models—0
BayesSpeech: A Bayesian Transformer Network for Automatic Speech Recognition—0
BayesPy: Variational Bayesian Inference in Python—0
Approximation-Aware Bayesian Optimization—0
Bayesian Variational Federated Learning and Unlearning in Decentralized Networks—0
Quantifying Variational Approximation for the Log-Partition Function—0
Einstein VI: General and Integrated Stein Variational Inference in NumPyro—0
Bayesian Transformer Language Models for Speech Recognition—0
Approximating exponential family models (not single distributions) with a two-network architecture—0
Efficient Transformed Gaussian Process State-Space Models for Non-Stationary High-Dimensional Dynamical Systems—0
A Generalization Bound for Online Variational Inference—0
Efficient Variational Bayes Learning of Graphical Models with Smooth Structural Changes—0
Approximate Probabilistic Inference with Composed Flows—0
Bayesian Crowdsourcing with Constraints—0
Streaming Adaptive Nonparametric Variational Autoencoder—0
Bayesian Robust Tensor Factorization for Incomplete Multiway Data—0
A Gaussian Process-Bayesian Bernoulli Mixture Model for Multi-Label Active Learning—0
Efficient Transformed Gaussian Processes for Non-Stationary Dependent Multi-class Classification—0
Large Skew-t Copula Models and Asymmetric Dependence in Intraday Equity Returns—0
Bayesian Probabilistic Matrix Factorization: A User Frequency Analysis—0
Bayesian Probabilistic Matrix Factorization—0
A Gaussian Process Based Method with Deep Kernel Learning for Pricing High-dimensional American Options—0
Bayesian Probabilistic Co-Subspace Addition—0
Approximate Inference for Spectral Mixture Kernel—0
Efficient Stein Variational Inference for Reliable Distribution-lossless Network Pruning—0
Efficient Training of Neural SDEs Using Stochastic Optimal Control—0
Bayesian posterior approximation via greedy particle optimization—0
Bayesian polynomial neural networks and polynomial neural ordinary differential equations—0
Efficient Reinforcement Learning with Large Language Model Priors—0
Bayesian Policy Search for Stochastic Domains—0
Efficient Semi-Implicit Variational Inference—0
Efficient transfer learning and online adaptation with latent variable models for continuous control—0
EigenVI: score-based variational inference with orthogonal function expansions—0
Endowing Robots with Longer-term Autonomy by Recovering from External Disturbances in Manipulation through Grounded Anomaly Classification and Recovery Policies—0
Bayesian Online Meta-Learning—0
Approximate Inference by Compilation to Arithmetic Circuits—0
Efficient EM-Variational Inference for Hawkes Process—0
Bayesian Nonparametric Reinforcement Learning in LTE and Wi-Fi Coexistence—0
Approximate Decentralized Bayesian Inference—0
A Framework for Variational Inference of Lightweight Bayesian Neural Networks with Heteroscedastic Uncertainties—0
Efficient Generative Modeling with Residual Vector Quantization-Based Tokens—0
Bayesian Nonparametric Modelling for Model-Free Reinforcement Learning in LTE-LAA and Wi-Fi Coexistence—0
Bayesian nonparametric comorbidity analysis of psychiatric disorders—0
Approximate Bayesian inference in spatial environments—0
Probabilistic Neural Transfer Function Estimation with Bayesian System Identification—0
Approximate Bayesian inference as a gauge theory—0
Efficient Correlated Topic Modeling with Topic Embedding—0
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