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

Triple-Hybrid Energy-based Model Makes Better Calibrated Natural Language Understanding Models EACL 2023
Why Out-of-Distribution detection experiments are not reliable - subtle experimental details muddle the OOD detector rankings UAI 2023
Logit-based ensemble distribution distillation for robust autoregressive sequence uncertainties UAI 2023
Birds of an odd feather: guaranteed out-of-distribution (OOD) novel category detection UAI 2023
In- or out-of-distribution detection via dual divergence estimation UAI 2023
Decoupling MaxLogit for Out-of-Distribution Detection CVPR 2023
LoCoOp: Few-Shot Out-of-Distribution Detection via Prompt Learning NIPS 2023
Out-of-Distributed Semantic Pruning for Robust Semi-Supervised Learning CVPR 2023
Improving Selective Visual Question Answering by Learning From Your Peers CVPR 2023
Improving Training and Inference of Face Recognition Models via Random Temperature Scaling AAAI 2023
Federated Learning with Uncertainty via Distilled Predictive Distributions ACML 2023
ActMAD: Activation Matching To Align Distributions for Test-Time-Training CVPR 2023
Know Your Space: Inlier and Outlier Construction for Calibrating Medical OOD Detectors MIDL 2023
Balanced Energy Regularization Loss for Out-of-Distribution Detection CVPR 2023
Reliability in Semantic Segmentation: Are We on the Right Track? CVPR 2023
CADet: Fully Self-Supervised Out-Of-Distribution Detection With Contrastive Learning NIPS 2023
Towards Building Self-Aware Object Detectors via Reliable Uncertainty Quantification and Calibration CVPR 2023
Deep Deterministic Uncertainty: A New Simple Baseline CVPR 2023
DARL: Distance-Aware Uncertainty Estimation for Offline Reinforcement Learning AAAI 2023
Adaptive Uncertainty Estimation via High-Dimensional Testing on Latent Representations NIPS 2023
Learning Sample Difficulty from Pre-trained Models for Reliable Prediction NIPS 2023
SELFOOD: Self-Supervised Out-Of-Distribution Detection via Learning to Rank EMNLP 2023
Optimal Parameter and Neuron Pruning for Out-of-Distribution Detection NIPS 2023
GradOrth: A Simple yet Efficient Out-of-Distribution Detection with Orthogonal Projection of Gradients NIPS 2023
Diversified Outlier Exposure for Out-of-Distribution Detection via Informative Extrapolation NIPS 2023