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Variational Inference

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Showing 651–700 of 2274 papers

TitleStatusHype
Rethinking Sharpness-Aware Minimization as Variational InferenceCode0
A Variational Perspective on Generative Flow Networks—0
On the Relationship Between Variational Inference and Auto-Associative MemoryCode0
Joint control variate for faster black-box variational inferenceCode0
Probabilistic Integration of Object Level Annotations in Chest X-ray Classification—0
Dirichlet process mixture models for non-stationary data streams—0
Alpha-divergence Variational Inference Meets Importance Weighted Auto-Encoders: Methodology and Asymptotics—0
Neural Extended Kalman Filters for Learning and Predicting Dynamics of Structural SystemsCode1
Latent Neural ODEs with Sparse Bayesian Multiple ShootingCode0
Leveraging Instance Features for Label Aggregation in Programmatic Weak SupervisionCode2
Few-shot Generation of Personalized Neural Surrogates for Cardiac Simulation via Bayesian Meta-LearningCode0
Scaling up Stochastic Gradient Descent for Non-convex Optimisation—0
Bayesian Prompt Learning for Image-Language Model GeneralizationCode1
Multi-view information fusion using multi-view variational autoencoders to predict proximal femoral strength—0
Uncertainty estimations methods for a deep learning model to aid in clinical decision-making -- a clinician's perspective—0
GFlowNets and variational inferenceCode0
Learnable Distribution Calibration for Few-Shot Class-Incremental Learning—0
Factorized Fusion Shrinkage for Dynamic Relational DataCode0
Cooperation in the Latent Space: The Benefits of Adding Mixture Components in Variational AutoencodersCode0
Structured Optimal Variational Inference for Dynamic Latent Space Models—0
Correcting the Sub-optimal Bit Allocation—0
Compositional Score Modeling for Simulation-based InferenceCode0
Targeted Separation and Convergence with Kernel Discrepancies—0
Variational Open-Domain Question AnsweringCode1
A Unified Perspective on Natural Gradient Variational Inference with Gaussian Mixture ModelsCode0
Jensen-Shannon Divergence Based Novel Loss Functions for Bayesian Neural NetworksCode0
Differentially private partitioned variational inferenceCode0
Amortized Variational Inference: A Systematic Review—0
Variational Inference for Infinitely Deep Neural NetworksCode1
Bit Allocation using OptimizationCode1
Adaptive Dimension Reduction and Variational Inference for Transductive Few-Shot Classification—0
Langevin Autoencoders for Learning Deep Latent Variable ModelsCode0
On the detrimental effect of invariances in the likelihood for variational inference—0
Fair Inference for Discrete Latent Variable Models—0
Modelling Technical and Biological Effects in scRNA-seq data with Scalable GPLVMsCode0
Structured Recognition for Generative Models with Explaining AwayCode0
CARE: Certifiably Robust Learning with Reasoning via Variational InferenceCode0
β-CapsNet: Learning Disentangled Representation for CapsNet by Information Bottleneck—0
Revisiting Active Sets for Gaussian Process DecodersCode0
A Variational Approach to Parameter Estimation for Characterizing 2-D Cluster Variation Method Topographies—0
Bayesian Neural Network Inference via Implicit Models and the Posterior Predictive Distribution—0
Variational Inference for Model-Free and Model-Based Reinforcement Learning—0
ProBoost: a Boosting Method for Probabilistic Classifiers—0
Learning Multiscale Non-stationary Causal Structures—0
Smoothness Analysis for Probabilistic Programs with Application to Optimised Variational InferenceCode0
Transductive Decoupled Variational Inference for Few-Shot ClassificationCode1
Cold Diffusion: Inverting Arbitrary Image Transforms Without NoiseCode3
Langevin Diffusion Variational Inference—0
Training Latent Variable Models with Auto-encoding Variational Bayes: A TutorialCode1
Uncertainty Quantification for Traffic Forecasting: A Unified Approach—0
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