{"total":46,"rows":[{"id":"2309.13415","title":"Dream the Impossible: Outlier Imagination with Diffusion Models","created":"2023-09-23","cited_by_count":77,"area":"diffusion"},{"id":"2302.10326","title":"Unsupervised Out-of-Distribution Detection with Diffusion Inpainting","created":"2023-02-20","cited_by_count":59,"area":"diffusion"},{"id":"2305.19643","title":"Mask, Stitch, and Re-Sample: Enhancing Robustness and Generalizability in Anomaly Detection through Automatic Diffusion Models","created":"2023-05-31","cited_by_count":50,"area":"diffusion"},{"id":"2303.03758","title":"Patched Diffusion Models for Unsupervised Anomaly Detection in Brain MRI","created":"2023-03-07","cited_by_count":45,"area":"diffusion"},{"id":"2308.07687","title":"DiffGuard: Semantic Mismatch-Guided Out-of-Distribution Detection using Pre-trained Diffusion Models","created":"2023-08-15","cited_by_count":26,"area":"diffusion"},{"id":"2307.03777","title":"Unsupervised 3D out-of-distribution detection with latent diffusion models","created":"2023-07-07","cited_by_count":22,"area":"diffusion"},{"id":"2404.15625","title":"Optimizing OOD Detection in Molecular Graphs: A Novel Approach with Diffusion Models","created":"2024-04-24","cited_by_count":22,"area":"diffusion"},{"id":"2405.11881","title":"Out-of-Distribution Detection with a Single Unconditional Diffusion Model","created":"2024-05-20","cited_by_count":22,"area":"diffusion"},{"id":"2312.04215","title":"Guided Reconstruction with Conditioned Diffusion Models for Unsupervised Anomaly Detection in Brain MRIs","created":"2023-12-07","cited_by_count":18,"area":"diffusion"},{"id":"2404.12667","title":"Detecting Out-Of-Distribution Earth Observation Images with Diffusion Models","created":"2024-04-19","cited_by_count":14,"area":"diffusion"},{"id":"2311.00469","title":"Dual Conditioned Diffusion Models for Out-Of-Distribution Detection: Application to Fetal Ultrasound Videos","created":"2023-11-01","cited_by_count":12,"area":"diffusion"},{"id":"2310.17432","title":"Likelihood-based Out-of-Distribution Detection with Denoising Diffusion Probabilistic Models","created":"2023-10-26","cited_by_count":10,"area":"diffusion"},{"id":"2502.16943","title":"MAD-AD: Masked Diffusion for Unsupervised Brain Anomaly Detection","created":"2025-02-24","cited_by_count":10,"area":"diffusion"},{"id":"2402.15516","title":"GLA-Grad: A Griffin-Lim Extended Waveform Generation Diffusion Model","created":"2024-02-09","cited_by_count":6,"area":"diffusion"},{"id":"2506.10233","title":"Conditional diffusion models for guided anomaly detection in brain images using fluid-driven anomaly randomization","created":"2025-06-11","cited_by_count":6,"area":"diffusion"},{"id":"2405.19201","title":"Going beyond Compositions, DDPMs Can Produce Zero-Shot Interpolations","created":"2024-05-29","cited_by_count":5,"area":"diffusion"},{"id":"2407.15169","title":"Back-in-Time Diffusion: Unsupervised Detection of Medical Deepfakes","created":"2024-07-21","cited_by_count":5,"area":"diffusion"},{"id":"2411.10701","title":"Diffusion-based Layer-wise Semantic Reconstruction for Unsupervised Out-of-Distribution Detection","created":"2024-11-16","cited_by_count":5,"area":"diffusion"},{"id":"2408.13623","title":"Prompt-Softbox-Prompt: A Free-Text Embedding Control for Image Editing","created":"2024-08-24","cited_by_count":4,"area":"diffusion"},{"id":"2505.11482","title":"Unsupervised Detection of Distribution Shift in Inverse Problems using Diffusion Models","created":"2025-05-16","cited_by_count":4,"area":"diffusion"},{"id":"2510.07206","title":"EigenScore: OOD Detection using Covariance in Diffusion Models","created":"2025-10-08","cited_by_count":4,"area":"diffusion"},{"id":"2307.06975","title":"Neuro-symbolic Empowered Denoising Diffusion Probabilistic Models for Real-time Anomaly Detection in Industry 4.0","created":"2023-07-13","cited_by_count":3,"area":"diffusion"},{"id":"2312.04382","title":"Adversarial Denoising Diffusion Model for Unsupervised Anomaly Detection","created":"2023-12-07","cited_by_count":3,"area":"diffusion"},{"id":"2510.01456","title":"SCOPED: Score-Curvature Out-of-distribution Proximity Evaluator for Diffusion","created":"2025-10-01","cited_by_count":3,"area":"diffusion"},{"id":"2310.08654","title":"Histogram- and Diffusion-Based Medical Out-of-Distribution Detection","created":"2023-10-12","cited_by_count":2,"area":"diffusion"},{"id":"2403.01485","title":"Approximations to the Fisher Information Metric of Deep Generative Models for Out-Of-Distribution Detection","created":"2024-03-03","cited_by_count":2,"area":"diffusion"},{"id":"2507.22692","title":"Zero-Shot Image Anomaly Detection Using Generative Foundation Models","created":"2025-07-30","cited_by_count":2,"area":"diffusion"},{"id":"2508.15737","title":"Probability Density from Latent Diffusion Models for Out-of-Distribution Detection","created":"2025-08-21","cited_by_count":2,"area":"diffusion"},{"id":"2406.16525","title":"Enhancing OOD Detection Using Latent Diffusion","created":"2024-06-24","cited_by_count":1,"area":"diffusion"},{"id":"2408.03654","title":"Unsupervised Detection of Fetal Brain Anomalies using Denoising Diffusion Models","created":"2024-08-07","cited_by_count":1,"area":"diffusion"},{"id":"2508.15236","title":"Pathology-Informed Latent Diffusion Model for Anomaly Detection in Lymph Node Metastasis","created":"2025-08-21","cited_by_count":1,"area":"diffusion"},{"id":"2509.18461","title":"Zero-Shot Visual Deepfake Detection: Can AI Predict and Prevent Fake Content Before It's Created?","created":"2025-09-22","cited_by_count":1,"area":"diffusion"},{"id":"2602.00191","title":"GEPC: Group-Equivariant Posterior Consistency for Out-of-Distribution Detection in Diffusion Models","created":"2026-01-30","cited_by_count":1,"area":"diffusion"},{"id":"2603.21717","title":"Uncertainty-Aware Distribution-to-Distribution Flow Matching for Scientific Imaging","created":"2026-03-23","cited_by_count":1,"area":"diffusion"},{"id":"2307.13949","title":"How Does Diffusion Influence Pretrained Language Models on Out-of-Distribution Data?","created":"2023-07-26","cited_by_count":0,"area":"diffusion"},{"id":"2405.00631","title":"Deep Metric Learning-Based Out-of-Distribution Detection with Synthetic Outlier Exposure","created":"2024-05-01","cited_by_count":0,"area":"diffusion"},{"id":"2409.01317","title":"LoGex: Improved tail detection of extremely rare histopathology classes via guided diffusion","created":"2024-09-02","cited_by_count":0,"area":"diffusion"},{"id":"2409.06364","title":"What happens to diffusion model likelihood when your model is conditional?","created":"2024-09-10","cited_by_count":0,"area":"diffusion"},{"id":"2409.10094","title":"Beyond Perceptual Distance: Discrepancy Assessment on Deep Representation for Out-of-Distribution Detection with Diffusion Model","created":"2024-09-16","cited_by_count":0,"area":"diffusion"},{"id":"2411.06308","title":"Exploring Out-of-distribution Detection for Sparse-view Computed Tomography with Diffusion Models","created":"2024-11-09","cited_by_count":0,"area":"diffusion"},{"id":"2508.03594","title":"CADD: Context aware disease deviations via restoration of brain images using normative conditional diffusion models","created":"2025-08-05","cited_by_count":0,"area":"diffusion"},{"id":"2510.13684","title":"Generating healthy counterfactuals with denoising diffusion bridge models","created":"2025-10-15","cited_by_count":0,"area":"diffusion"},{"id":"2511.21863","title":"Saddle-Free Guidance: Improved On-Manifold Sampling without Labels or Additional Training","created":"2025-11-26","cited_by_count":0,"area":"diffusion"},{"id":"2602.13061","title":"Native Extrapolation Awareness in Flow-Based Conditional Generation","created":"2026-02-13","cited_by_count":0,"area":"diffusion"},{"id":"2604.00283","title":"Data-Driven Reachability Analysis via Diffusion Models with PAC Guarantees","created":"2026-03-31","cited_by_count":0,"area":"diffusion"},{"id":"2605.20502","title":"Tippett-minimum Fusion of Representation-space Diffusion Models for Multi-Encoder Out-of-Distribution Detection","created":"2026-05-19","cited_by_count":0,"area":"diffusion"}],"next_cursor":null}