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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 401–450 of 629 papers

TitleStatusHype
Optimizing Latent Dimension Allocation in Hierarchical VAEs: Balancing Attenuation and Information Retention for OOD Detection—0
OT-DETECTOR: Delving into Optimal Transport for Zero-shot Out-of-Distribution Detection—0
What do we learn? Debunking the Myth of Unsupervised Outlier Detection—0
Out-of-distribution detection algorithms for robust insect classification—0
Out-of-Distribution Detection and Data Drift Monitoring using Statistical Process Control—0
Out-of-Distribution Detection and Selective Generation for Conditional Language Models—0
Federated Learning with Uncertainty via Distilled Predictive Distributions—0
Batch-Ensemble Stochastic Neural Networks for Out-of-Distribution Detection—0
Out-of-distribution Partial Label Learning—0
Out of distribution detection for intra-operative functional imaging—0
Out-of-Distribution Detection for LiDAR-based 3D Object Detection—0
Trustworthy Personalized Bayesian Federated Learning via Posterior Fine-Tune—0
TTA-OOD: Test-time Augmentation for Improving Out-of-Distribution Detection in Gastrointestinal Vision—0
Out of distribution detection for skin and malaria images—0
Out of Distribution Detection, Generalization, and Robustness Triangle with Maximum Probability Theorem—0
Two-step counterfactual generation for OOD examples—0
Out-of-Distribution Detection in Dermatology using Input Perturbation and Subset Scanning—0
Out-of-distribution Detection in Medical Image Analysis: A survey—0
Out-of-Distribution Detection in Multi-Label Datasets using Latent Space of β-VAE—0
BAM: Box Abstraction Monitors for Real-time OoD Detection in Object Detection—0
Out-Of-Distribution Detection In Unsupervised Continual Learning—0
Out-Of-Distribution Detection Is Not All You Need—0
UFO: Unidentified Foreground Object Detection in 3D Point Cloud—0
Out-of-Distribution Detection of Melanoma using Normalizing Flows—0
Uncertainty-Aware Multiple-Instance Learning for Reliable Classification: Application to Optical Coherence Tomography—0
Out-of-Distribution Detection Should Use Conformal Prediction (and Vice-versa?)—0
Out-of-Distribution Detection Using Neural Rendering Generative Models—0
Out-of-Distribution Detection Using Peer-Class Generated by Large Language Model—0
Detecting when pre-trained nnU-Net models fail silently for Covid-19 lung lesion segmentation—0
Detecting Out-of-Distribution Examples with Gram Matrices—0
Detecting Out-of-distribution Examples via Class-conditional Impressions Reappearing—0
Out-of-Distribution Detection with Reconstruction Error and Typicality-based Penalty—0
A Variational Information Theoretic Approach to Out-of-Distribution Detection—0
A Unified Approach Towards Active Learning and Out-of-Distribution Detection—0
Detecting Compositionally Out-of-Distribution Examples in Semantic Parsing—0
Out-of-Distribution Detection with Class Ratio Estimation—0
Detecting Anomalous Event Sequences with Temporal Point Processes—0
Out-of-Distribution Detection with Overlap Index—0
Detecting and Learning Out-of-Distribution Data in the Open world: Algorithm and Theory—0
Out-Of-Distribution Detection With Subspace Techniques And Probabilistic Modeling Of Features—0
Uncertainty-based Meta-Reinforcement Learning for Robust Radar Tracking—0
Out-of-distribution multi-view auto-encoders for prostate cancer lesion detection—0
Out of Distribution Reasoning by Weakly-Supervised Disentangled Logic Variational Autoencoder—0
Out-of-domain Detection based on Generative Adversarial Network—0
A Baseline for Detecting Out-of-Distribution Examples in Image Captioning—0
Density of States Estimation for Out-of-Distribution Detection—0
Overcoming Shortcut Problem in VLM for Robust Out-of-Distribution Detection—0
Deep Neural Network Identification of Limnonectes Species and New Class Detection Using Image Data—0
PnPOOD : Out-Of-Distribution Detection for Text Classification via Plug andPlay Data Augmentation—0
Deep Metric Learning-Based Out-of-Distribution Detection with Synthetic Outlier Exposure—0
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