SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 401–450 of 629 papers

TitleStatusHype
Beyond Mahalanobis-Based Scores for Textual OOD Detection—0
Diffusion Denoising Process for Perceptron Bias in Out-of-distribution DetectionCode0
Towards Realistic Out-of-Distribution Detection: A Novel Evaluation Framework for Improving Generalization in OOD DetectionCode0
A Benchmark for Out of Distribution Detection in Point Cloud 3D Semantic Segmentation—0
Estimating Soft Labels for Out-of-Domain Intent Detection—0
Interpreting deep learning output for out-of-distribution detection—0
Understanding the properties and limitations of contrastive learning for Out-of-Distribution detection—0
Exploring Structure-Wise Uncertainty for 3D Medical Image Segmentation—0
On Out-of-Distribution Detection for Audio with Deep Nearest NeighborsCode0
Is Out-of-Distribution Detection Learnable?—0
Uncertainty-based Meta-Reinforcement Learning for Robust Radar Tracking—0
Falsehoods that ML researchers believe about OOD detection—0
Enhancing Out-of-Distribution Detection in Natural Language Understanding via Implicit Layer EnsembleCode0
UniNL: Aligning Representation Learning with Scoring Function for OOD Detection via Unified Neighborhood LearningCode0
Disentangling the Predictive Variance of Deep Ensembles through the Neural Tangent Kernel—0
An out-of-distribution discriminator based on Bayesian neural network epistemic uncertainty—0
Out of Distribution Reasoning by Weakly-Supervised Disentangled Logic Variational Autoencoder—0
Disentangling Confidence Score Distribution for Out-of-Domain Intent Detection with Energy-Based LearningCode0
Pseudo-OOD training for robust language models—0
Holistic Sentence Embeddings for Better Out-of-Distribution Detection—0
Exploiting Mixed Unlabeled Data for Detecting Samples of Seen and Unseen Out-of-Distribution Classes—0
OpenOOD: Benchmarking Generalized Out-of-Distribution DetectionCode0
How to Enable Uncertainty Estimation in Proximal Policy Optimization—0
A Novel Explainable Out-of-Distribution Detection Approach for Spiking Neural NetworksCode0
Out-of-Distribution Detection and Selective Generation for Conditional Language Models—0
Out-of-Distribution Detection for LiDAR-based 3D Object Detection—0
Raising the Bar on the Evaluation of Out-of-Distribution Detection—0
Linking Neural Collapse and L2 Normalization with Improved Out-of-Distribution Detection in Deep Neural Networks—0
Topological Structure Learning for Weakly-Supervised Out-of-Distribution Detection—0
Distribution Calibration for Out-of-Domain Detection with Bayesian ApproximationCode0
Fine-grain Inference on Out-of-Distribution Data with Hierarchical Classification—0
Improving Out-of-Distribution Detection via Epistemic Uncertainty Adversarial Training—0
Identifying Out-of-Distribution Samples in Real-Time for Safety-Critical 2D Object Detection with Margin Entropy Loss—0
Probing Contextual Diversity for Dense Out-of-Distribution DetectionCode0
Open-Set Semi-Supervised Object Detection—0
Contrastive Learning for OOD in Object detectionCode0
Efficient Out-of-Distribution Detection of Melanoma with Wavelet-based Normalizing FlowsCode0
Distance-based detection of out-of-distribution silent failures for Covid-19 lung lesion segmentation—0
Curved Geometric Networks for Visual Anomaly Recognition—0
XOOD: Extreme Value Based Out-Of-Distribution Detection For Image ClassificationCode0
A Novel Data Augmentation Technique for Out-of-Distribution Sample Detection using Compounded CorruptionsCode0
Task Agnostic and Post-hoc Unseen Distribution Detection—0
Instance-Aware Observer Network for Out-of-Distribution Object Segmentation—0
A Simple Test-Time Method for Out-of-Distribution Detection—0
On the Usefulness of Deep Ensemble Diversity for Out-of-Distribution DetectionCode0
Sample-dependent Adaptive Temperature Scaling for Improved CalibrationCode0
Know Your Space: Inlier and Outlier Construction for Calibrating Medical OOD Detectors—0
A Baseline for Detecting Out-of-Distribution Examples in Image Captioning—0
Out-of-Distribution Detection in Time-Series Domain: A Novel Seasonal Ratio Scoring ApproachCode0
Harnessing Out-Of-Distribution Examples via Augmenting Content and StyleCode0
Show:102550
← PrevPage 9 of 13Next →

No leaderboard results yet.