Cover Image

A Variational Information Theoretic Approach to Out-of-Distribution Detection

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Mondal, Sudeepta, Jiang, Zhuolin, Sundaramoorthi, Ganesh
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Tuning Out-of-Distribution (OOD) Detectors Without Given OOD Data
by: Mondal, Sudeepta, et al.
Published: (2026)

Non-intrusive Learning of Physics-Informed Spatio-temporal Surrogate for Accelerating Design
by: Mondal, Sudeepta, et al.
Published: (2026)

DKL-KAN: Scalable Deep Kernel Learning using Kolmogorov-Arnold Networks
by: Zinage, Shrenik, et al.
Published: (2024)

A PDE-based Explanation of Extreme Numerical Sensitivities and Edge of Stability in Training Neural Networks
by: Sun, Yuxin, et al.
Published: (2022)

A Bayesian approach to quantifying uncertainties and improving generalizability in traffic prediction models
by: Sengupta, Agnimitra, et al.
Published: (2023)

Unsupervised Out-of-Distribution Detection by Restoring Lossy Inputs with Variational Autoencoder
by: Zeng, Zezhen, et al.
Published: (2023)

Out-of-Distribution Detection on Graphs: A Survey
by: Cai, Tingyi, et al.
Published: (2025)

A Sharper Global Convergence Analysis for Average Reward Reinforcement Learning via an Actor-Critic Approach
by: Ganesh, Swetha, et al.
Published: (2024)

Out-of-Distribution Radar Detection in Compound Clutter and Thermal Noise through Variational Autoencoders
by: Rouzoumka, Y A, et al.
Published: (2025)

ODE-GS: Latent ODEs for Dynamic Scene Extrapolation with 3D Gaussian Splatting
by: Wang, Daniel, et al.
Published: (2025)

Enclosing Prototypical Variational Autoencoder for Explainable Out-of-Distribution Detection
by: Orglmeister, Conrad, et al.
Published: (2025)

Federated Adapter on Foundation Models: An Out-Of-Distribution Approach
by: Yang, Yiyuan, et al.
Published: (2025)

DOS: Diverse Outlier Sampling for Out-of-Distribution Detection
by: Jiang, Wenyu, et al.
Published: (2023)

Order-Optimal Regret with Novel Policy Gradient Approaches in Infinite-Horizon Average Reward MDPs
by: Ganesh, Swetha, et al.
Published: (2024)

An Information-Theoretic Framework for Out-of-Distribution Generalization with Applications to Stochastic Gradient Langevin Dynamics
by: Liu, Wenliang, et al.
Published: (2024)

Out-of-Distribution Detection with Overlap Index
by: Fu, Hao, et al.
Published: (2024)

Kernel PCA for Out-of-Distribution Detection
by: Fang, Kun, et al.
Published: (2024)

What Information Matters? Graph Out-of-Distribution Detection via Tri-Component Information Decomposition
by: Wang, Danny, et al.
Published: (2026)

Disentangled Graph Prompting for Out-Of-Distribution Detection
by: Yang, Cheng, et al.
Published: (2026)

Perturb-and-Compare Approach for Detecting Out-of-Distribution Samples in Constrained Access Environments
by: Lee, Heeyoung, et al.
Published: (2024)

A Closer Look at the Learnability of Out-of-Distribution (OOD) Detection
by: Garov, Konstantin, et al.
Published: (2025)

When and How Does In-Distribution Label Help Out-of-Distribution Detection?
by: Du, Xuefeng, et al.
Published: (2024)

A Mixture of Exemplars Approach for Efficient Out-of-Distribution Detection with Foundation Models
by: Mannix, Evelyn, et al.
Published: (2023)

Out-of-Distribution Detection Methods Answer the Wrong Questions
by: Li, Yucen Lily, et al.
Published: (2025)

Improving Out-of-Distribution Detection with Markov Logic Networks
by: Kirchheim, Konstantin, et al.
Published: (2025)

Optimal Parameter and Neuron Pruning for Out-of-Distribution Detection
by: Chen, Chao, et al.
Published: (2024)

Uncertainty-Aware Out-of-Distribution Detection with Gaussian Processes
by: Chen, Yang, et al.
Published: (2024)

The Challenge of Out-Of-Distribution Detection in Motor Imagery BCIs
by: Mulder, Merlijn Quincent, et al.
Published: (2026)

AP-OOD: Attention Pooling for Out-of-Distribution Detection
by: Hofmann, Claus, et al.
Published: (2026)

AHA: Human-Assisted Out-of-Distribution Generalization and Detection
by: Bai, Haoyue, et al.
Published: (2024)

Unifying Unsupervised Graph-Level Anomaly Detection and Out-of-Distribution Detection: A Benchmark
by: Wang, Yili, et al.
Published: (2024)

A Bayesian Nonparametric Perspective on Mahalanobis Distance for Out of Distribution Detection
by: Linderman, Randolph W., et al.
Published: (2025)

Large Language Models for Anomaly and Out-of-Distribution Detection: A Survey
by: Xu, Ruiyao, et al.
Published: (2024)

Out-of-Distribution Detection: A Task-Oriented Survey of Recent Advances
by: Lu, Shuo, et al.
Published: (2024)

An Information-Theoretic Approach to Generalization Theory
by: Rodríguez-Gálvez, Borja, et al.
Published: (2024)

VNDUQE: Information-Theoretic Novelty Detection using Deep Variational Information Bottleneck
by: Gondkar, Aryan, et al.
Published: (2026)

Redundancy-Aware Test-Time Graph Out-of-Distribution Detection
by: Hou, Yue, et al.
Published: (2025)

RankOOD -- Class Ranking-based Out-of-Distribution Detection
by: Denipitiyage, Dishanika, et al.
Published: (2025)

Domain Feature Collapse: Implications for Out-of-Distribution Detection and Solutions
by: Yang, Hong, et al.
Published: (2025)

Sharpness-Aware Geometric Defense for Robust Out-Of-Distribution Detection
by: Li, Jeng-Lin, et al.
Published: (2025)