SOTAVerified

Variational Inference

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1251–1300 of 2274 papers

TitleStatusHype
Generalized Variational Continual Learning—0
Parametric Bootstrap Ensembles as Variational Inference—0
Generative Video Compression as Hierarchical Variational Inference—0
Gaussian Process Latent Variable Flows for Massively Missing Data—0
Gaussian Density Parametrization Flow: Particle and Stochastic Approaches—0
Scalable Hybrid Hidden Markov Model with Gaussian Process Emission for Sequential Time-series Observations—0
Neural Linear Models with Functional Gaussian Process Priors—0
The Gaussian Process Latent Autoregressive Model—0
Gradient Regularisation as Approximate Variational Inference—0
Rethinking Function-Space Variational Inference in Bayesian Neural Networks—0
On the Inconsistency of Bayesian Inference for Misspecified Neural Networks—0
Marginal Likelihood Gradient for Bayesian Neural Networks—0
Variational Refinement for Importance SamplingUsing the Forward Kullback-Leibler Divergence—0
Online Learning Based Risk-Averse Stochastic MPC of Constrained Linear Uncertain Systems—0
Variational Laplace for Bayesian neural networks—0
Understanding Variational Inference in Function-SpaceCode0
Recursive Inference for Variational Autoencoders—0
Efficient Variational Inference for Sparse Deep Learning with Theoretical GuaranteeCode0
Dirichlet Pruning for Neural Network CompressionCode0
Sparse within Sparse Gaussian Processes using Neighbor Information—0
Reward Conditioned Neural Movement Primitives for Population Based Variational Policy OptimizationCode0
Multi-output Gaussian Process Modulated Poisson Processes for Event Prediction—0
Quantized Variational InferenceCode0
Learning a Generative Motion Model from Image Sequences based on a Latent Motion Matrix—0
Amortized Variational Deep Q NetworkCode0
On Signal-to-Noise Ratio Issues in Variational Inference for Deep Gaussian ProcessesCode0
Hyperbolic Graph Embedding with Enhanced Semi-Implicit Variational InferenceCode0
Meaningful uncertainties from deep neural network surrogates of large-scale numerical simulations—0
Latent Network Estimation and Variable Selection for Compositional Data via Variational EMCode0
Statistical optimality and stability of tangent transform algorithms in logit models—0
Variational Bayesian Unlearning—0
Out-of-distribution detection for regression tasks: parameter versus predictor entropy—0
Nearly Optimal Variational Inference for High Dimensional Regression with Shrinkage Priors—0
Statistical Guarantees for Transformation Based Models with Applications to Implicit Variational Inference—0
UNITE: Uncertainty-based Health Risk Prediction Leveraging Multi-sourced Data—0
The Role of Mutual Information in Variational Classifiers—0
Sparse Gaussian Process Variational AutoencodersCode0
Semi-parametric γ-ray modeling with Gaussian processes and variational inferenceCode0
Learning to Learn Variational Semantic MemoryCode0
Privacy-preserving Data Sharing on Vertically Partitioned Data—0
Directed Variational Cross-encoder Network for Few-shot Multi-image Co-segmentation—0
Ensemble Kalman Variational Objectives: Nonlinear Latent Trajectory Inference with A Hybrid of Variational Inference and Ensemble Kalman FilterCode0
Variational Dynamic for Self-Supervised Exploration in Deep Reinforcement Learning—0
Generating Diverse Translation from Model Distribution with Dropout—0
Flexible mean field variational inference using mixtures of non-overlapping exponential familiesCode0
Tensor Train Factorization and Completion under Noisy Data with Prior Analysis and Rank EstimationCode0
Variational Feature Disentangling for Fine-Grained Few-Shot Classification—0
Narrative Text Generation with a Latent Discrete PlanCode0
Learning from demonstration using products of experts: applications to manipulation and task prioritization—0
VCDM: Leveraging Variational Bi-encoding and Deep Contextualized Word Representations for Improved Definition ModelingCode0
Show:102550
← PrevPage 26 of 46Next →

No leaderboard results yet.