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Out-of-Distribution Detection

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하위 태스크: 0
평가표: 53
보존된 평가 기록: 269

Detect out-of-distribution or anomalous examples.

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/emannix/tintem-teacher-in-the-middle

공식 코드

Faithful Label-free Knowledge Distillation

https://github.com/engkarat/cosine-ood-detector

공식 코드

Hyperparameter-Free Out-of-Distribution Detection Using Softmax of Scaled Cosine Similarity

https://github.com/ensta-u2is/dido

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Discretization-Induced Dirichlet Posterior for Robust Uncertainty Quantification on Regression

https://github.com/ericpts/reto

공식 코드

Semi-supervised novelty detection using ensembles with regularized disagreement

https://github.com/ethancaballero/broken_neural_scaling_laws

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Broken Neural Scaling Laws

https://github.com/evihuijben/ood_detection_mri

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Enhancing Reconstruction-Based Out-of-Distribution Detection in Brain MRI with Model and Metric Ensembles

https://github.com/facebookresearch/odin

공식 코드

Enhancing The Reliability of Out-of-distribution Image Detection in Neural Networks

https://github.com/fair4hep/pfin4uqad

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Evidential Deep Learning for Uncertainty Quantification and Out-of-Distribution Detection in Jet Identification using Deep Neural Networks

https://github.com/fanghenshaometeor/ood-kernel-pca

공식 코드

Kernel PCA for Out-of-Distribution Detection

https://github.com/fanghenshaometeor/ood-kpca-extension

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Kernel PCA for Out-of-Distribution Detection: Non-Linear Kernel Selections and Approximations

https://github.com/fanghenshaometeor/ood-mode-ensemble

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Revisiting Deep Ensemble for Out-of-Distribution Detection: A Loss Landscape Perspective

https://github.com/felime/autoseg

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AutoSeg -- Steering the Inductive Biases for Automatic Pathology Segmentation

https://github.com/fir-lat/hamos_ood

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Outlier Synthesis via Hamiltonian Monte Carlo for Out-of-Distribution Detection

https://github.com/fiveai/saod

공식 코드

Towards Building Self-Aware Object Detectors via Reliable Uncertainty Quantification and Calibration

https://github.com/fjelenic/between-layer-ood

공식 코드

Out-of-Distribution Detection by Leveraging Between-Layer Transformation Smoothness

https://github.com/forblindrev/aibias

공식 코드

Fair and accurate age prediction using distribution aware data curation and augmentation

https://github.com/francescopinto/regmixup

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RegMixup: Mixup as a Regularizer Can Surprisingly Improve Accuracy and Out Distribution Robustness

https://github.com/frederikwarburg/laplaceae

공식 코드

Laplacian Autoencoders for Learning Stochastic Representations

https://github.com/fregu856/regression_uncertainty

공식 코드

How Reliable is Your Regression Model's Uncertainty Under Real-World Distribution Shifts?

https://github.com/frejberglind/xood

공식 코드

XOOD: Extreme Value Based Out-Of-Distribution Detection For Image Classification

https://github.com/g-pichler/in_feasibility_of_ml_backdoor_detection

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On the (In)feasibility of ML Backdoor Detection as an Hypothesis Testing Problem

https://github.com/gfloto/tilted_prior

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The Exponentially Tilted Gaussian Prior for Variational Autoencoders

https://github.com/giacomo97cnr/rule-based-odd

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Rule-based Out-Of-Distribution Detection

https://github.com/giataile/realoecl

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Understanding normalization in contrastive representation learning and out-of-distribution detection

https://github.com/gicheonkang/gst-visdial

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The Dialog Must Go On: Improving Visual Dialog via Generative Self-Training

https://github.com/giovannicina/selecting_ood_detector

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Out-of-Distribution Detection for Medical Applications: Guidelines for Practical Evaluation

https://github.com/gist-ailab/block-selection-for-ood-detection

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Block Selection Method for Using Feature Norm in Out-of-distribution Detection

https://github.com/glhr/beyond-auroc

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Beyond AUROC & co. for evaluating out-of-distribution detection performance

https://github.com/gmr523/pop

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Out-of-Distribution Detection with Prototypical Outlier Proxy

https://github.com/google-research/google-research

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Likelihood Ratios for Out-of-Distribution Detection

https://github.com/google/uncertainty-baselines

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A Simple Fix to Mahalanobis Distance for Improving Near-OOD Detection

https://github.com/gudovskiy/flowenedet

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Concurrent Misclassification and Out-of-Distribution Detection for Semantic Segmentation via Energy-Based Normalizing Flow

https://github.com/guoxoug/ens-div-ood-detect

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On the Usefulness of Deep Ensemble Diversity for Out-of-Distribution Detection

https://github.com/guyAmit/GLOD

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FOOD: Fast Out-Of-Distribution Detector

https://github.com/haiyunyao/diversemix

공식 코드

Out-Of-Distribution Detection with Diversification (Provably)

https://github.com/haoliangwang86/la-ood

공식 코드

Layer Adaptive Deep Neural Networks for Out-of-distribution Detection

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