Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 461 to 470 of 213,137 articles

In-Context Time Series Classification with Random Convolutional Features

arXiv Jul 21, 2026
Time series classification is central to domains like medical signal analysis, industrial monitoring, and sensor-based activity recognition, where class information manifests as localized shapes, specific frequencies, temporal shifts, or complex cros... read more 
Machine Learning

PathAgentBench: Benchmarking Evidence-Seeking Vision-Language Models on Whole-Slide Pathology Image

arXiv Jul 21, 2026
Whole-slide image (WSI) diagnosis requires identifying diagnostically relevant regions, examining them across magnifications, and integrating multi-scale evidence. However, most existing pathology benchmarks evaluate models on pre-cropped patches or ... read more 
Computer Vision and Pattern Recognition cs.AI

Riemannian Deep Learning:Modules, Networks, and Geometries

arXiv Jul 21, 2026
Deep neural networks on manifold-valued representations have attracted growing interest, but many basic components remain tied to specific manifolds, rely on Euclidean approximations, or require costly and numerically fragile geometric operations. Th... read more 
Machine Learning cs.AI math.DG

ERank in Latent Space as an Image-Complexity and Richness Measure

arXiv Jul 21, 2026
We propose the effective rank (ERank) of the channel covariance of an image's deep feature map as a per-sample, label-free measure of visual richness, computed from a single forward pass through a frozen pretrained encoder. ERank counts how many deco... read more 
Computer Vision and Pattern Recognition

InstructMixup: Instruction-Guided Salient Patch Editing for Robust Data Augmentation

arXiv Jul 21, 2026
In image and video technologies, data augmentation is widely used to improve the generalization of deep visual models, and mixup-based strategies that interpolate between samples have become the dominant approach. However, computing informative mixin... read more 
Computer Vision and Pattern Recognition

Provable diffusion-based posterior sampling for linear inverse problems via DDIM

arXiv Jul 21, 2026
Diffusion-based methods have achieved remarkable empirical success in solving inverse problems. However, many existing posterior samplers either lack rigorous theoretical guarantees or incur substantial computational overhead. We propose a simple and... read more 
Machine Learning cs.AI stat.ML

ExpertVerse: A General-Purpose Benchmark for Expert-Level Reasoning in Knowledge-Intensive Visual Synthesis

arXiv Jul 21, 2026
Recent advances in multimodal generative models have enabled instruction-based image generation to move beyond semantic manipulation to knowledge-driven visual reasoning. However, these methods focus on explicit commonsense reasoning, shallow causal ... read more 
Computer Vision and Pattern Recognition

Appearance Pointers -- Multimodal Region Control of Diffusion Transformers

arXiv Jul 21, 2026
Controllable image generation remains challenging for creative professionals, who often require precise regional control over materials, object identities, and spatial arrangements that cannot be reliably achieved through text prompting alone. Diffus... read more 
Computer Vision and Pattern Recognition cs.AI cs.GR

Unlearning as Distribution Restoration: A Controlled Counterfactual Study, a Validated Selective Screen, and the Limits of Oracle-Free Certification

arXiv Jul 21, 2026
Machine unlearning is commonly evaluated by matching a retrained oracle on trained probes. In a controlled nonce-fact testbed with a matched retraining reference, we find this criterion can favor methods that retain held-out knowledge: candidates it ... read more 
Machine Learning cs.AI

Marine Engine Fault Dataset: Open-Access Data under Controlled Reference and Fault Scenario Conditions

arXiv Jul 21, 2026
Open-access datasets for marine-engine predictive maintenance remain scarce, particularly those from controlled fault experiments with documented operating conditions, subsystem-level interventions and system-level measurements. This work presents th... read more 
Machine Learning eess.SP eess.SY
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