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Out of Distribution (OOD) Detection

Out of Distribution (OOD) Detection is the task of detecting instances that do not belong to the distribution the classifier has been trained on. OOD data is often referred to as "unseen" data, as the model has not encountered it during training.

OOD detection is typically performed by training a model to distinguish between in-distribution (ID) data, which the model has seen during training, and OOD data, which it has not seen. This can be done using a variety of techniques, such as training a separate OOD detector, or modifying the model's architecture or loss function to make it more sensitive to OOD data.

Papers

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Showing 551–600 of 629 papers

TitleStatusHype
Improving Calibration and Out-of-Distribution Detection in Medical Image Segmentation with Convolutional Neural NetworksCode0
AUTO: Adaptive Outlier Optimization for Test-Time OOD DetectionCode0
Weak Distribution Detectors Lead to Stronger Generalizability of Vision-Language Prompt TuningCode0
Improvements on Uncertainty Quantification for Node Classification via Distance-Based RegularizationCode0
ImageNet-OOD: Deciphering Modern Out-of-Distribution Detection AlgorithmsCode0
OpenOOD: Benchmarking Generalized Out-of-Distribution DetectionCode0
Igeood: An Information Geometry Approach to Out-of-Distribution DetectionCode0
CVAD: A generic medical anomaly detector based on Cascade VAECode0
Uncertainty-Guided Appearance-Motion Association Network for Out-of-Distribution Action DetectionCode0
Open-World Lifelong Graph LearningCode0
XOOD: Extreme Value Based Out-Of-Distribution Detection For Image ClassificationCode0
Analysis of Confident-Classifiers for Out-of-distribution DetectionCode0
Outlier Synthesis via Hamiltonian Monte Carlo for Out-of-Distribution DetectionCode0
Structural Entropy Guided Unsupervised Graph Out-Of-Distribution DetectionCode0
Adversarial Self-Supervised Learning for Out-of-Domain DetectionCode0
A Bayesian Nonparametric Perspective on Mahalanobis Distance for Out of Distribution DetectionCode0
Out-of-distribution detection based on subspace projection of high-dimensional features output by the last convolutional layerCode0
Out-of-Distribution Detection based on In-Distribution Data Patterns Memorization with Modern Hopfield EnergyCode0
Out-of-Distribution Detection by Leveraging Between-Layer Transformation SmoothnessCode0
T2FNorm: Extremely Simple Scaled Train-time Feature Normalization for OOD DetectionCode0
TagOOD: A Novel Approach to Out-of-Distribution Detection via Vision-Language Representations and Class Center LearningCode0
Out-of-Distribution Detection for Long-tailed and Fine-grained Skin Lesion ImagesCode0
Out-of-Distribution Detection for Medical Applications: Guidelines for Practical EvaluationCode0
Contrastive Learning for OOD in Object detectionCode0
What If the Input is Expanded in OOD Detection?Code0
Out-of-distribution Detection in Classifiers via GenerationCode0
Task-Driven Detection of Distribution Shifts with Statistical Guarantees for Robot LearningCode0
Taylor Outlier ExposureCode0
Towards Realistic Out-of-Distribution Detection: A Novel Evaluation Framework for Improving Generalization in OOD DetectionCode0
Out-of-Distribution Detection in Time-Series Domain: A Novel Seasonal Ratio Scoring ApproachCode0
Adapting Contrastive Language-Image Pretrained (CLIP) Models for Out-of-Distribution DetectionCode0
Contextual Out-of-Domain Utterance Handling With Counterfeit Data AugmentationCode0
Out-of-distribution Detection Learning with Unreliable Out-of-distribution SourcesCode0
When and How Does In-Distribution Label Help Out-of-Distribution Detection?Code0
Out of Distribution Detection on ImageNet-OCode0
Are Bayesian neural networks intrinsically good at out-of-distribution detection?Code0
UniNL: Aligning Representation Learning with Scoring Function for OOD Detection via Unified Neighborhood LearningCode0
Approximations to the Fisher Information Metric of Deep Generative Models for Out-Of-Distribution DetectionCode0
Identifying Incorrect Classifications with Balanced UncertaintyCode0
Hybrid Energy Based Model in the Feature Space for Out-of-Distribution DetectionCode0
Harnessing Out-Of-Distribution Examples via Augmenting Content and StyleCode0
A Novel Explainable Out-of-Distribution Detection Approach for Spiking Neural NetworksCode0
Out-Of-Distribution Detection with Diversification (Provably)Code0
Out-of-Distribution Detection with Prototypical Outlier ProxyCode0
HALO: Robust Out-of-Distribution Detection via Joint OptimisationCode0
Advancing Out-of-Distribution Detection via Local NeuroplasticityCode0
Gradient-Regularized Out-of-Distribution DetectionCode0
Unsupervised Energy-based Out-of-distribution Detection using Stiefel-Restricted Kernel MachineCode0
Going Beyond Conventional OOD DetectionCode0
Toward Metrics for Differentiating Out-of-Distribution SetsCode0
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