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Out of Distribution (OOD) Detection
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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.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/anthropics/hh-rlhf
공식 코드Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback
https://github.com/anugyas/ood-on-nae
공식 코드https://github.com/atsumiyai/gl-mcm
공식 코드GL-MCM: Global and Local Maximum Concept Matching for Zero-Shot Out-of-Distribution Detection
https://github.com/atsumiyai/locoop
공식 코드LoCoOp: Few-Shot Out-of-Distribution Detection via Prompt Learning
https://github.com/atsumiyai/pt-ood
공식 코드Can Pre-trained Networks Detect Familiar Out-of-Distribution Data?
https://github.com/awenbocc/llm-ood
공식 코드https://github.com/bach05/SOODImageNet
공식 코드https://github.com/bhattarailab/ncdd
공식 코드NCDD: Nearest Centroid Distance Deficit for Out-Of-Distribution Detection in Gastrointestinal Vision
https://github.com/bobowner/open-world-lgl
공식 코드https://github.com/borchero/natural-posterior-network
공식 코드Natural Posterior Network: Deep Bayesian Uncertainty for Exponential Family Distributions
https://github.com/borisshirokikh/mood_submission_sample-level_airi
공식 코드Solving Sample-Level Out-of-Distribution Detection on 3D Medical Images
https://github.com/chrhenning/uncertainty_based_ood
공식 코드On out-of-distribution detection with Bayesian neural networks
https://github.com/christophbrgr/ood_detection_framework
공식 코드Confidence-based Out-of-Distribution Detection: A Comparative Study and Analysis
https://github.com/cleanlab/cleanlab
공식 코드Back to the Basics: Revisiting Out-of-Distribution Detection Baselines
https://github.com/cleanlab/ood-detection-benchmarks
공식 코드Back to the Basics: Revisiting Out-of-Distribution Detection Baselines
https://github.com/clear-nus/diffpath
공식 코드Out-of-Distribution Detection with a Single Unconditional Diffusion Model
https://github.com/cnc-ood/cnc_ood
공식 코드https://github.com/corl-team/sdde
공식 코드https://github.com/cps-research-group/cps-ntu-public
공식 코드Demo Abstract: Real-Time Out-of-Distribution Detection on a Mobile Robot
https://github.com/cure-lab/moodcat
공식 코드Out-of-Distribution Detection with Semantic Mismatch under Masking
https://github.com/czgdp1807/pTrustIntervalsOOD
공식 코드Probabilistic Trust Intervals for Out of Distribution Detection
https://github.com/deeplearning-wisc/MOOD
공식 코드https://github.com/deeplearning-wisc/cider
공식 코드How to Exploit Hyperspherical Embeddings for Out-of-Distribution Detection?
https://github.com/deeplearning-wisc/dice
공식 코드DICE: Leveraging Sparsification for Out-of-Distribution Detection
https://github.com/deeplearning-wisc/dream-ood
공식 코드Dream the Impossible: Outlier Imagination with Diffusion Models
https://github.com/deeplearning-wisc/id_label
공식 코드When and How Does In-Distribution Label Help Out-of-Distribution Detection?
https://github.com/deeplearning-wisc/multi-label-ood
공식 코드Can multi-label classification networks know what they don't know?
https://github.com/deeplearning-wisc/poem
공식 코드https://github.com/deeplearning-wisc/spurious_ood
공식 코드On the Impact of Spurious Correlation for Out-of-distribution Detection
https://github.com/deeplearning-wisc/stud
공식 코드Unknown-Aware Object Detection: Learning What You Don't Know from Videos in the Wild
https://github.com/deeplearning-wisc/vos
공식 코드VOS: Learning What You Don't Know by Virtual Outlier Synthesis
https://github.com/deepmind/jax_verify
공식 코드Make Sure You're Unsure: A Framework for Verifying Probabilistic Specifications
https://github.com/devd1092/ood-skin-lesion
공식 코드Out-of-Distribution Detection for Long-tailed and Fine-grained Skin Lesion Images
https://github.com/dheeraj7596/selfood
공식 코드SELFOOD: Self-Supervised Out-Of-Distribution Detection via Learning to Rank
https://github.com/digitaldigger/bayesianvaesood
공식 코드Do Bayesian Variational Autoencoders Know What They Don't Know?
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