{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/task/out-of-distribution-detection/papers/7","list_of":"/task/out-of-distribution-detection","task":"Out-of-Distribution Detection","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":7,"pages_in_order":9,"rows_per_page":100,"rows":[601,700],"of":888,"counts":{"archive_papers_tagged":888,"with_a_code_link":438,"where_syntology_ran_a_sample":181,"not_listed_spam_title":0,"listed":888,"listed_where_code_ran":181,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":146,"every_run_a_failure_of_syntologys_instrument":35,"listed_with_a_run_with_no_instrument_failure":146,"listed_every_run_a_failure_of_syntologys_instrument":35,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/out-of-distribution-detection","prev":"/task/out-of-distribution-detection/papers/6","next":"/task/out-of-distribution-detection/papers/8","papers":[{"url":null,"slug":"a-novel-statistical-measure-for-out-of","title":"A Novel Statistical Measure for Out-of-Distribution Detection in Data Quality Assurance","date":"2023-10-12","arxiv_id":"2310.07998","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-large-language-models-for-multi","title":"Exploring Large Language Models for Multi-Modal Out-of-Distribution Detection","date":"2023-10-12","arxiv_id":"2310.08027","repositories_listed":0,"syntology":null},{"url":null,"slug":"histogram-and-diffusion-based-medical-out-of","title":"Histogram- and Diffusion-Based Medical Out-of-Distribution Detection","date":"2023-10-12","arxiv_id":"2310.08654","repositories_listed":0,"syntology":null},{"url":null,"slug":"see-ood-supervised-exploration-for-enhanced","title":"SEE-OoD: Supervised Exploration For Enhanced Out-of-Distribution Detection","date":"2023-10-12","arxiv_id":"2310.08040","repositories_listed":0,"syntology":null},{"url":null,"slug":"understanding-the-feature-norm-for-out-of-1","title":"Understanding the Feature Norm for Out-of-Distribution Detection","date":"2023-10-09","arxiv_id":"2310.05316","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-a-disentangling-representation-for","title":"Learning A Disentangling Representation For PU Learning","date":"2023-10-05","arxiv_id":"2310.03833","repositories_listed":0,"syntology":null},{"url":null,"slug":"openpatch-a-3d-patchwork-for-out-of","title":"OpenPatch: a 3D patchwork for Out-Of-Distribution detection","date":"2023-10-05","arxiv_id":"2310.03388","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-metacognitive-approach-to-out-of","title":"A Metacognitive Approach to Out-of-Distribution Detection for Segmentation","date":"2023-10-04","arxiv_id":"2311.07578","repositories_listed":0,"syntology":null},{"url":null,"slug":"you-can-have-your-ensemble-and-run-it-too","title":"You can have your ensemble and run it too -- Deep Ensembles Spread Over Time","date":"2023-09-20","arxiv_id":"2309.11333","repositories_listed":0,"syntology":null},{"url":null,"slug":"bea-revisiting-anchor-based-object-detection","title":"BEA: Revisiting anchor-based object detection DNN using Budding Ensemble Architecture","date":"2023-09-14","arxiv_id":"2309.08036","repositories_listed":0,"syntology":null},{"url":null,"slug":"out-of-distribution-detection-via-domain","title":"Out of Distribution Detection via Domain-Informed Gaussian Process State Space Models","date":"2023-09-13","arxiv_id":"2309.06655","repositories_listed":0,"syntology":null},{"url":null,"slug":"hact-out-of-distribution-detection-with","title":"HAct: Out-of-Distribution Detection with Neural Net Activation Histograms","date":"2023-09-09","arxiv_id":"2309.04837","repositories_listed":0,"syntology":null},{"url":null,"slug":"probabilistic-self-supervised-learning-via","title":"Probabilistic Self-supervised Learning via Scoring Rules Minimization","date":"2023-09-05","arxiv_id":"2309.02048","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-automated-and-early-detection-of","title":"Enhancing Automated and Early Detection of Alzheimer's Disease Using Out-Of-Distribution Detection","date":"2023-09-04","arxiv_id":"2309.01312","repositories_listed":0,"syntology":null},{"url":null,"slug":"echocardiographic-view-classification-with","title":"Improving Out-of-Distribution Detection in Echocardiographic View Classication through Enhancing Semantic Features","date":"2023-08-31","arxiv_id":"2308.16483","repositories_listed":0,"syntology":null},{"url":null,"slug":"diversified-ensemble-of-independent-sub","title":"Diversified Ensemble of Independent Sub-Networks for Robust Self-Supervised Representation Learning","date":"2023-08-28","arxiv_id":"2308.14705","repositories_listed":0,"syntology":null},{"url":null,"slug":"out-of-distribution-detection-using","title":"Out-of-distribution detection using normalizing flows on the data manifold","date":"2023-08-26","arxiv_id":"2308.13792","repositories_listed":0,"syntology":null},{"url":null,"slug":"graph-neural-stochastic-differential-1","title":"Graph Neural Stochastic Differential Equations","date":"2023-08-23","arxiv_id":"2308.12316","repositories_listed":0,"syntology":null},{"url":null,"slug":"hierarchical-uncertainty-estimation-for","title":"Hierarchical Uncertainty Estimation for Medical Image Segmentation Networks","date":"2023-08-16","arxiv_id":"2308.08465","repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-out-of-distribution-dialect","title":"Unsupervised Out-of-Distribution Dialect Detection with Mahalanobis Distance","date":"2023-08-09","arxiv_id":"2308.04886","repositories_listed":0,"syntology":null},{"url":null,"slug":"dynamic-model-agnostic-reliability-evaluation","title":"Dynamic Model Agnostic Reliability Evaluation of Machine-Learning Methods Integrated in Instrumentation & Control Systems","date":"2023-08-08","arxiv_id":"2308.05120","repositories_listed":0,"syntology":null},{"url":null,"slug":"msac-multiple-speech-attribute-control-method","title":"MSAC: Multiple Speech Attribute Control Method for Reliable Speech Emotion Recognition","date":"2023-08-08","arxiv_id":"2308.04025","repositories_listed":0,"syntology":null},{"url":null,"slug":"redesigning-out-of-distribution-detection-on","title":"Redesigning Out-of-Distribution Detection on 3D Medical Images","date":"2023-08-07","arxiv_id":"2308.07324","repositories_listed":0,"syntology":null},{"url":null,"slug":"diversify-a-general-framework-for-time-series","title":"DIVERSIFY: A General Framework for Time Series Out-of-distribution Detection and Generalization","date":"2023-08-04","arxiv_id":"2308.02282","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-probabilistic-approach-to-self-supervised","title":"A Probabilistic Approach to Self-Supervised Learning using Cyclical Stochastic Gradient MCMC","date":"2023-08-02","arxiv_id":"2308.01271","repositories_listed":0,"syntology":null},{"url":null,"slug":"three-factors-to-improve-out-of-distribution","title":"Three Factors to Improve Out-of-Distribution Detection","date":"2023-08-02","arxiv_id":"2308.01030","repositories_listed":0,"syntology":null},{"url":null,"slug":"gradorth-a-simple-yet-efficient-out-of","title":"GradOrth: A Simple yet Efficient Out-of-Distribution Detection with Orthogonal Projection of Gradients","date":"2023-08-01","arxiv_id":"2308.00310","repositories_listed":0,"syntology":null},{"url":null,"slug":"mim-ood-generative-masked-image-modelling-for","title":"MIM-OOD: Generative Masked Image Modelling for Out-of-Distribution Detection in Medical Images","date":"2023-07-27","arxiv_id":"2307.14701","repositories_listed":0,"syntology":null},{"url":null,"slug":"hood-real-time-robust-human-presence-and-out","title":"HOOD: Real-Time Human Presence and Out-of-Distribution Detection Using FMCW Radar","date":"2023-07-24","arxiv_id":"2308.02396","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-holistic-assessment-of-the-reliability-of","title":"A Holistic Assessment of the Reliability of Machine Learning Systems","date":"2023-07-20","arxiv_id":"2307.10586","repositories_listed":0,"syntology":null},{"url":null,"slug":"pseudo-outlier-exposure-for-out-of","title":"Pseudo Outlier Exposure for Out-of-Distribution Detection using Pretrained Transformers","date":"2023-07-18","arxiv_id":"2307.09455","repositories_listed":0,"syntology":null},{"url":null,"slug":"reject-option-models-comprising-out-of","title":"Reject option models comprising out-of-distribution detection","date":"2023-07-11","arxiv_id":"2307.05199","repositories_listed":0,"syntology":null},{"url":null,"slug":"stylegan2-based-out-of-distribution-detection","title":"StyleGAN2-based Out-of-Distribution Detection for Medical Imaging","date":"2023-07-10","arxiv_id":"2307.10193","repositories_listed":0,"syntology":null},{"url":null,"slug":"end-to-end-out-of-distribution-detection-with","title":"Image Background Serves as Good Proxy for Out-of-distribution Data","date":"2023-07-02","arxiv_id":"2307.00519","repositories_listed":0,"syntology":null},{"url":null,"slug":"limitations-of-out-of-distribution-detection","title":"Limitations of Out-of-Distribution Detection in 3D Medical Image Segmentation","date":"2023-06-23","arxiv_id":"2306.13528","repositories_listed":0,"syntology":null},{"url":null,"slug":"training-diffusion-classifiers-with-denoising","title":"DiffAug: A Diffuse-and-Denoise Augmentation for Training Robust Classifiers","date":"2023-06-15","arxiv_id":"2306.09192","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-unnormalized-statistical-models-via","title":"Learning Unnormalized Statistical Models via Compositional Optimization","date":"2023-06-13","arxiv_id":"2306.07485","repositories_listed":0,"syntology":null},{"url":null,"slug":"how-does-fine-tuning-impact-out-of","title":"How Does Fine-Tuning Impact Out-of-Distribution Detection for Vision-Language Models?","date":"2023-06-09","arxiv_id":"2306.06048","repositories_listed":0,"syntology":null},{"url":null,"slug":"simple-high-quality-ood-detection-with-l2","title":"Exploring Simple, High Quality Out-of-Distribution Detection with L2 Normalization","date":"2023-06-07","arxiv_id":"2306.04072","repositories_listed":0,"syntology":null},{"url":null,"slug":"sr-ood-out-of-distribution-detection-via","title":"SR-OOD: Out-of-Distribution Detection via Sample Repairing","date":"2023-05-26","arxiv_id":"2305.18228","repositories_listed":0,"syntology":null},{"url":null,"slug":"logit-based-ensemble-distribution","title":"Logit-Based Ensemble Distribution Distillation for Robust Autoregressive Sequence Uncertainties","date":"2023-05-17","arxiv_id":"2305.10384","repositories_listed":0,"syntology":null},{"url":null,"slug":"out-of-distribution-detection-for-adaptive","title":"Out-of-Distribution Detection for Adaptive Computer Vision","date":"2023-05-16","arxiv_id":"2305.09293","repositories_listed":0,"syntology":null},{"url":null,"slug":"uncertainty-estimation-for-deep-learning","title":"Uncertainty Estimation and Out-of-Distribution Detection for Deep Learning-Based Image Reconstruction using the Local Lipschitz","date":"2023-05-12","arxiv_id":"2305.07618","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-survey-on-out-of-distribution-detection-in","title":"A Survey on Out-of-Distribution Detection in NLP","date":"2023-05-05","arxiv_id":"2305.03236","repositories_listed":0,"syntology":null},{"url":null,"slug":"out-of-distribution-detection-algorithms-for","title":"Out-of-distribution detection algorithms for robust insect classification","date":"2023-05-02","arxiv_id":"2305.01823","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-sample-difficulty-from-pre-trained","title":"Learning Sample Difficulty from Pre-trained Models for Reliable Prediction","date":"2023-04-20","arxiv_id":"2304.10127","repositories_listed":0,"syntology":null},{"url":null,"slug":"unified-out-of-distribution-detection-a-model","title":"Unified Out-Of-Distribution Detection: A Model-Specific Perspective","date":"2023-04-13","arxiv_id":"2304.06813","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-anti-regularized-ensembles-provide","title":"Deep Anti-Regularized Ensembles provide reliable out-of-distribution uncertainty quantification","date":"2023-04-08","arxiv_id":"2304.04042","repositories_listed":0,"syntology":null},{"url":null,"slug":"multimodal-neural-processes-for-uncertainty","title":"Beyond Unimodal: Generalising Neural Processes for Multimodal Uncertainty Estimation","date":"2023-04-04","arxiv_id":"2304.01518","repositories_listed":0,"syntology":null},{"url":null,"slug":"non-generative-energy-based-models","title":"Non-Generative Energy Based Models","date":"2023-04-03","arxiv_id":"2304.01297","repositories_listed":0,"syntology":null},{"url":null,"slug":"establishing-baselines-and-introducing","title":"Establishing baselines and introducing TernaryMixOE for fine-grained out-of-distribution detection","date":"2023-03-30","arxiv_id":"2303.17658","repositories_listed":0,"syntology":null},{"url":null,"slug":"nearest-neighbor-based-out-of-distribution","title":"Nearest Neighbor Based Out-of-Distribution Detection in Remote Sensing Scene Classification","date":"2023-03-29","arxiv_id":"2303.16616","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-global-model-approach-to-robust-few-shot","title":"A Global Model Approach to Robust Few-Shot SAR Automatic Target Recognition","date":"2023-03-20","arxiv_id":"2303.10800","repositories_listed":0,"syntology":null},{"url":null,"slug":"inpl-pseudo-labeling-the-inliers-first-for","title":"InPL: Pseudo-labeling the Inliers First for Imbalanced Semi-supervised Learning","date":"2023-03-13","arxiv_id":"2303.07269","repositories_listed":0,"syntology":null},{"url":null,"slug":"mcrood-multi-class-radar-out-of-distribution","title":"MCROOD: Multi-Class Radar Out-Of-Distribution Detection","date":"2023-03-10","arxiv_id":"2303.06232","repositories_listed":0,"syntology":null},{"url":null,"slug":"predicted-embedding-power-regression-for","title":"Predicted Embedding Power Regression for Large-Scale Out-of-Distribution Detection","date":"2023-03-07","arxiv_id":"2303.04115","repositories_listed":0,"syntology":null},{"url":null,"slug":"how-to-construct-energy-for-images-denoising","title":"How to Construct Energy for Images? Denoising Autoencoder Can Be Energy Based Model","date":"2023-03-05","arxiv_id":"2303.03887","repositories_listed":0,"syntology":null},{"url":null,"slug":"average-of-pruning-improving-performance-and","title":"Average of Pruning: Improving Performance and Stability of Out-of-Distribution Detection","date":"2023-03-02","arxiv_id":"2303.01201","repositories_listed":0,"syntology":null},{"url":null,"slug":"reconstruction-based-out-of-distribution","title":"Reconstruction-based Out-of-Distribution Detection for Short-Range FMCW Radar","date":"2023-02-27","arxiv_id":"2302.14192","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-efficient-method-for-out-of-distribution","title":"VRA: Variational Rectified Activation for Out-of-distribution Detection","date":"2023-02-23","arxiv_id":"2302.11716","repositories_listed":0,"syntology":null},{"url":null,"slug":"steerable-equivariant-representation-learning","title":"Steerable Equivariant Representation Learning","date":"2023-02-22","arxiv_id":"2302.11349","repositories_listed":0,"syntology":null},{"url":null,"slug":"malprotect-stateful-defense-against","title":"MalProtect: Stateful Defense Against Adversarial Query Attacks in ML-based Malware Detection","date":"2023-02-21","arxiv_id":"2302.10739","repositories_listed":0,"syntology":null},{"url":null,"slug":"variational-boosted-soft-trees","title":"Variational Boosted Soft Trees","date":"2023-02-21","arxiv_id":"2302.10706","repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-evaluation-of-out-of","title":"Unsupervised Evaluation of Out-of-distribution Detection: A Data-centric Perspective","date":"2023-02-16","arxiv_id":"2302.08287","repositories_listed":0,"syntology":null},{"url":null,"slug":"uncertainty-estimation-with-normalized-logits","title":"Uncertainty-Estimation with Normalized Logits for Out-of-Distribution Detection","date":"2023-02-15","arxiv_id":"2302.07608","repositories_listed":0,"syntology":null},{"url":null,"slug":"robustness-to-spurious-correlations-improves","title":"Robustness to Spurious Correlations Improves Semantic Out-of-Distribution Detection","date":"2023-02-08","arxiv_id":"2302.04132","repositories_listed":0,"syntology":null},{"url":null,"slug":"cluster-aware-contrastive-learning-for","title":"Cluster-aware Contrastive Learning for Unsupervised Out-of-distribution Detection","date":"2023-02-06","arxiv_id":"2302.02598","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-to-reject-meets-ood-detection-are","title":"Plugin estimators for selective classification with out-of-distribution detection","date":"2023-01-29","arxiv_id":"2301.12386","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-data-centric-approach-for-improving","title":"A Data-Centric Approach for Improving Adversarial Training Through the Lens of Out-of-Distribution Detection","date":"2023-01-25","arxiv_id":"2301.10454","repositories_listed":0,"syntology":null},{"url":null,"slug":"interpretable-out-of-distribution-detection","title":"Interpretable Out-Of-Distribution Detection Using Pattern Identification","date":"2023-01-24","arxiv_id":"2302.10303","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-multi-scale-framework-for-out-of","title":"A Multi-Scale Framework for Out-of-Distribution Detection in Dermoscopic Images","date":"2023-01-18","arxiv_id":"2301.07533","repositories_listed":0,"syntology":null},{"url":"/paper/decoupling-maxlogit-for-out-of-distribution","slug":"decoupling-maxlogit-for-out-of-distribution","title":"Decoupling MaxLogit for Out-of-Distribution Detection","date":"2023-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"probabilistic-knowledge-distillation-of-face","title":"Probabilistic Knowledge Distillation of Face Ensembles","date":"2023-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"simple-and-effective-out-of-distribution","title":"Simple and Effective Out-of-Distribution Detection via Cosine-based Softmax Loss","date":"2023-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"out-of-distribution-detection-with","title":"Out-of-Distribution Detection with Reconstruction Error and Typicality-based Penalty","date":"2022-12-24","arxiv_id":"2212.12641","repositories_listed":0,"syntology":null},{"url":null,"slug":"runtime-monitoring-for-out-of-distribution","title":"Runtime Monitoring for Out-of-Distribution Detection in Object Detection Neural Networks","date":"2022-12-15","arxiv_id":"2212.07773","repositories_listed":0,"syntology":null},{"url":null,"slug":"rethinking-out-of-distribution-detection-from","title":"Rethinking Out-of-Distribution Detection From a Human-Centric Perspective","date":"2022-11-30","arxiv_id":"2211.16778","repositories_listed":0,"syntology":null},{"url":null,"slug":"out-of-distribution-detection-is-not-all-you","title":"Out-Of-Distribution Detection Is Not All You Need","date":"2022-11-29","arxiv_id":"2211.16158","repositories_listed":0,"syntology":null},{"url":null,"slug":"diffusion-denoising-process-for-perceptron","title":"Diffusion Denoising Process for Perceptron Bias in Out-of-distribution Detection","date":"2022-11-21","arxiv_id":"2211.11255","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-benchmark-for-out-of-distribution-detection","title":"A Benchmark for Out of Distribution Detection in Point Cloud 3D Semantic Segmentation","date":"2022-11-11","arxiv_id":"2211.06241","repositories_listed":0,"syntology":null},{"url":null,"slug":"disentangled-uncertainty-and-out-of","title":"Disentangled Uncertainty and Out of Distribution Detection in Medical Generative Models","date":"2022-11-11","arxiv_id":"2211.06250","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-uncertainty-based-out-of","title":"Improving Uncertainty-based Out-of-Distribution Detection for Medical Image Segmentation","date":"2022-11-10","arxiv_id":"2211.05421","repositories_listed":0,"syntology":null},{"url":null,"slug":"interpreting-deep-learning-output-for-out-of","title":"Interpreting deep learning output for out-of-distribution detection","date":"2022-11-07","arxiv_id":"2211.03637","repositories_listed":0,"syntology":null},{"url":null,"slug":"understanding-the-properties-and-limitations","title":"Understanding the properties and limitations of contrastive learning for Out-of-Distribution detection","date":"2022-11-06","arxiv_id":"2211.03183","repositories_listed":0,"syntology":null},{"url":null,"slug":"is-out-of-distribution-detection-learnable","title":"Is Out-of-Distribution Detection Learnable?","date":"2022-10-26","arxiv_id":"2210.14707","repositories_listed":0,"syntology":null},{"url":null,"slug":"bridging-machine-learning-and-sciences","title":"Bridging Machine Learning and Sciences: Opportunities and Challenges","date":"2022-10-24","arxiv_id":"2210.13441","repositories_listed":0,"syntology":null},{"url":null,"slug":"uncertainty-estimation-for-out-of","title":"Uncertainty estimation for out-of-distribution detection in computational histopathology","date":"2022-10-18","arxiv_id":"2210.09909","repositories_listed":0,"syntology":null},{"url":null,"slug":"uncertainty-in-extreme-multi-label","title":"Uncertainty in Extreme Multi-label Classification","date":"2022-10-18","arxiv_id":"2210.10160","repositories_listed":0,"syntology":null},{"url":"/paper/boosting-out-of-distribution-detection-with","slug":"boosting-out-of-distribution-detection-with","title":"Boosting Out-of-distribution Detection with Typical Features","date":"2022-10-09","arxiv_id":"2210.04200","repositories_listed":0,"syntology":null},{"url":null,"slug":"ai-driven-road-maintenance-inspection-v2","title":"AI-Driven Road Maintenance Inspection v2: Reducing Data Dependency & Quantifying Road Damage","date":"2022-10-07","arxiv_id":"2210.03570","repositories_listed":0,"syntology":null},{"url":null,"slug":"out-of-distribution-detection-and-selective","title":"Out-of-Distribution Detection and Selective Generation for Conditional Language Models","date":"2022-09-30","arxiv_id":"2209.15558","repositories_listed":0,"syntology":null},{"url":null,"slug":"out-of-distribution-detection-for-lidar-based","title":"Out-of-Distribution Detection for LiDAR-based 3D Object Detection","date":"2022-09-28","arxiv_id":"2209.14435","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-comprehensive-review-of-trends-applications","title":"A Comprehensive Review of Trends, Applications and Challenges In Out-of-Distribution Detection","date":"2022-09-26","arxiv_id":"2209.12935","repositories_listed":0,"syntology":null},{"url":null,"slug":"raising-the-bar-on-the-evaluation-of-out-of","title":"Raising the Bar on the Evaluation of Out-of-Distribution Detection","date":"2022-09-24","arxiv_id":"2209.11960","repositories_listed":0,"syntology":null},{"url":null,"slug":"two-stage-modeling-for-prediction-with","title":"Two-stage Modeling for Prediction with Confidence","date":"2022-09-19","arxiv_id":"2209.08848","repositories_listed":0,"syntology":null},{"url":null,"slug":"inducing-early-neural-collapse-in-deep-neural","title":"Linking Neural Collapse and L2 Normalization with Improved Out-of-Distribution Detection in Deep Neural Networks","date":"2022-09-17","arxiv_id":"2209.08378","repositories_listed":0,"syntology":null},{"url":null,"slug":"topological-structure-learning-for-weakly","title":"Topological Structure Learning for Weakly-Supervised Out-of-Distribution Detection","date":"2022-09-16","arxiv_id":"2209.07837","repositories_listed":0,"syntology":null},{"url":null,"slug":"smood-smoothness-based-out-of-distribution","title":"SmOOD: Smoothness-based Out-of-Distribution Detection Approach for Surrogate Neural Networks in Aircraft Design","date":"2022-09-07","arxiv_id":"2209.03438","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-out-of-distribution-detection-via","title":"Improving Out-of-Distribution Detection via Epistemic Uncertainty Adversarial Training","date":"2022-09-05","arxiv_id":"2209.03148","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-in-distribution-compatibility-in-out","title":"Towards In-distribution Compatibility in Out-of-distribution Detection","date":"2022-08-29","arxiv_id":"2208.13433","repositories_listed":0,"syntology":null}],"record_sha256":"a732bee5210d2c0491f21eafab332047a31acb042144e9832b4aff5a6cb6fb91","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}