conftrace_

out-of-distribution detection

617 papers

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Also known as

OODD OOD DETECTION

Co-occurring keywords

uncertainty quantification (1393) distribution shift (722) uncertainty estimation (648) anomaly detection (747) neural network (6616) ood detection (45) generative model (2892) representation learning (6206) domain generalization (1522) contrastive learning (4032)

Papers

Exploiting Mixed Unlabeled Data for Detecting Samples of Seen and Unseen Out-of-Distribution Classes AAAI 2022
Uncertainty Estimation of Transformer Predictions for Misclassification Detection ACL 2022
Improving Evidential Deep Learning via Multi-Task Learning AAAI 2022
Learning Confidence for Transformer-based Neural Machine Translation ACL 2022
On Continual Model Refinement in Out-of-Distribution Data Streams ACL 2022
Investigating Selective Prediction Approaches Across Several Tasks in IID, OOD, and Adversarial Settings ACL 2022
Evaluating the Practical Utility of Confidence-score based Techniques for Unsupervised Open-world Classification ACL 2022
Training OOD Detectors in their Natural Habitats ICML 2022
Out of Distribution Data Detection Using Dropout Bayesian Neural Networks AAAI 2022
Do Bayesian variational autoencoders know what they don’t know? UAI 2022
Semi-supervised novelty detection using ensembles with regularized disagreement UAI 2022
End-to-End Open-Set Semi-Supervised Node Classification with Out-of-Distribution Detection IJCAI 2022
Deep Combinatorial Aggregation NIPS 2022
UQGAN: A Unified Model for Uncertainty Quantification of Deep Classifiers trained via Conditional GANs NIPS 2022
Model-agnostic out-of-distribution detection using combined statistical tests AISTATS 2022
SIREN: Shaping Representations for Detecting Out-of-Distribution Objects NIPS 2022
DIBS: Diversity Inducing Information Bottleneck in Model Ensembles AAAI 2021
Towards optimally abstaining from prediction with OOD test examples NIPS 2021
A Geometric Perspective towards Neural Calibration via Sensitivity Decomposition NIPS 2021
Can multi-label classification networks know what they don’t know? NIPS 2021
Natural Adversarial Examples CVPR 2021
Topological Uncertainty: Monitoring Trained Neural Networks through Persistence of Activation Graphs IJCAI 2021
Likelihood-free Out-of-Distribution Detection with Invertible Generative Models IJCAI 2021
ReAct: Out-of-distribution Detection With Rectified Activations NIPS 2021
Exploring the Limits of Out-of-Distribution Detection NIPS 2021