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Variational Inference

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TitleStatusHype
Bayesian Online Meta-Learning—0
Bayesian Policy Search for Stochastic Domains—0
Bayesian polynomial neural networks and polynomial neural ordinary differential equations—0
Bayesian posterior approximation via greedy particle optimization—0
Bayesian Probabilistic Co-Subspace Addition—0
Bayesian Probabilistic Matrix Factorization—0
Bayesian Probabilistic Matrix Factorization: A User Frequency Analysis—0
Bayesian Robust Tensor Factorization for Incomplete Multiway Data—0
Bayesian Crowdsourcing with Constraints—0
Bayesian Transformer Language Models for Speech Recognition—0
Bayesian Variational Federated Learning and Unlearning in Decentralized Networks—0
BayesPy: Variational Bayesian Inference in Python—0
BayesSpeech: A Bayesian Transformer Network for Automatic Speech Recognition—0
β-CapsNet: Learning Disentangled Representation for CapsNet by Information Bottleneck—0
Benchmarking common uncertainty estimation methods with histopathological images under domain shift and label noise—0
Benefits of Overparameterization in Single-Layer Latent Variable Generative Models—0
Beta Process Multiple Kernel Learning—0
Beta Process Non-negative Matrix Factorization with Stochastic Structured Mean-Field Variational Inference—0
Bethe Projections for Non-Local Inference—0
Dissecting Non-Vacuous Generalization Bounds based on the Mean-Field Approximation—0
Beyond black-boxes in Bayesian inverse problems and model validation: applications in solid mechanics of elastography—0
Beyond Rewards: a Hierarchical Perspective on Offline Multiagent Behavioral Analysis—0
Black-Box Autoregressive Density Estimation for State-Space Models—0
Black-Box Variational Inference as a Parametric Approximation to Langevin Dynamics—0
Blind Channel Estimation for MIMO Systems via Variational Inference—0
Blind Image Denoising via Dependent Dirichlet Process Tree—0
Blindness of score-based methods to isolated components and mixing proportions—0
BoA-PTA, A Bayesian Optimization Accelerated Error-Free SPICE Solver—0
Boosting Variational Inference—0
Boosting Variational Inference: an Optimization Perspective—0
Boosting Variational Inference With Locally Adaptive Step-Sizes—0
B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and Inverse PDE Problems with Noisy Data—0
A Survey on Brain-Inspired Deep Learning via Predictive Coding—0
Brain in the Dark: Design Principles for Neuro-mimetic Learning and Inference—0
Branching Stein Variational Gradient Descent for sampling multimodal distributions—0
Bridging the inference gap in Mutimodal Variational Autoencoders—0
B-SCST: Bayesian Self-Critical Sequence Training for Image Captioning—0
Building Bayesian Neural Networks with Blocks: On Structure, Interpretability and Uncertainty—0
C^2INet: Realizing Incremental Trajectory Prediction with Prior-Aware Continual Causal Intervention—0
Calibration of Model Uncertainty for Dropout Variational Inference—0
Categories and Functional Units: An Infinite Hierarchical Model for Brain Activations—0
CausalMMM: Learning Causal Structure for Marketing Mix Modeling—0
Causal Semantic Communication for Digital Twins: A Generalizable Imitation Learning Approach—0
Causal View of Time Series Imputation: Some Identification Results on Missing Mechanism—0
Celeste: Variational inference for a generative model of astronomical images—0
Central Limit Theorem for Bayesian Neural Network trained with Variational Inference—0
CG-BERT: Conditional Text Generation with BERT for Generalized Few-shot Intent Detection—0
Challenges and Opportunities in High-dimensional Variational Inference—0
Challenges and Opportunities in High Dimensional Variational Inference—0
Challenges and Pitfalls of Bayesian Unlearning—0
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