SOTAVerified

Variational Inference

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1001–1050 of 2274 papers

TitleStatusHype
Composing Normalizing Flows for Inverse Problems—0
Amortized Context Vector Inference for Sequence-to-Sequence Networks—0
Hamiltonian Policy Optimization in Reinforcement Learning—0
Interpretable Operational Risk Classification with Semi-Supervised Variational Autoencoder—0
Hamiltonian Policy Optimization—0
An Equivalence between Bayesian Priors and Penalties in Variational Inference—0
Half-VAE: An Encoder-Free VAE to Bypass Explicit Inverse Mapping—0
Introducing instance label correlation in multiple instance learning. Application to cancer detection on histopathological images—0
Introducing Routing Uncertainty in Capsule Networks—0
Investigating maximum likelihood based training of infinite mixtures for uncertainty quantification—0
ISAM-MTL: Cross-subject multi-task learning model with identifiable spikes and associative memory networks—0
ISA-VAE: Independent Subspace Analysis with Variational Autoencoders—0
Is MC Dropout Bayesian?—0
Isometric Gaussian Process Latent Variable Model for Dissimilarity Data—0
Half-AVAE: Adversarial-Enhanced Factorized and Structured Encoder-Free VAE for Underdetermined Independent Component Analysis—0
Group Factor Analysis—0
Gray-box inference for structured Gaussian process models—0
Neural Graph Collaborative Filtering Using Variational Inference—0
Concurrent Training and Layer Pruning of Deep Neural Networks—0
Amortized Bayesian Meta-Learning—0
A Deep Variational Bayesian Framework for Blind Image Deblurring—0
Joint Modeling of Visual Objects and Relations for Scene Graph Generation—0
A Bayesian Detect to Track System for Robust Visual Object Tracking and Semi-Supervised Model Learning—0
Distance-Preserving Spatial Representations in Genomic Data—0
PGODE: Towards High-quality System Dynamics Modeling—0
Computing with Categories in Machine Learning—0
Gradients should stay on Path: Better Estimators of the Reverse- and Forward KL Divergence for Normalizing Flows—0
AutoBayes: A Compositional Framework for Generalized Variational Inference—0
Gradient Regularisation as Approximate Variational Inference—0
Variational Laplace for Bayesian neural networks—0
Compositional Scene Modeling with Global Object-Centric Representations—0
AUTM Flow: Atomic Unrestricted Time Machine for Monotonic Normalizing Flows—0
Amortized backward variational inference in nonlinear state-space models—0
Gradient-based inference of abstract task representations for generalization in neural networks—0
GRADE: Graph Dynamic Embedding—0
GP-ALPS: Automatic Latent Process Selection for Multi-Output Gaussian Process Models—0
Good Initializations of Variational Bayes for Deep Models—0
Complex Inference in Neural Circuits with Probabilistic Population Codes and Topic Models—0
A universal probabilistic spike count model reveals ongoing modulation of neural variability—0
Amortised MAP Inference for Image Super-resolution—0
Global Approximate Inference via Local Linearisation for Temporal Gaussian Processes—0
GFlowOut: Dropout with Generative Flow Networks—0
Complementary Information Mutual Learning for Multimodality Medical Image Segmentation—0
Geometric variational inference—0
Geometric Dirichlet Means algorithm for topic inference—0
Comparing the quality of neural network uncertainty estimates for classification problems—0
A Unified Framework for Entropy Search and Expected Improvement in Bayesian Optimization—0
Generative Video Compression as Hierarchical Variational Inference—0
Generative Temporal Models with Memory—0
Combining Random Walks and Nonparametric Bayesian Topic Model for Community Detection—0
Show:102550
← PrevPage 21 of 46Next →

No leaderboard results yet.