Can scientists detect life without knowing what it looks like? Research using machine learning offers a new way

If nonliving materials can produce rich, organized mixtures of organic molecules, then the traditional signs we use to ...
Unite.AI

The Reinforcement Gap: Why AI Excels at Some Tasks but Stalls at Others

Artificial Intelligence (AI) has achieved remarkable successes in recent years. It can defeat human champions in games like Go, predict protein structures with high accuracy, and perform complex tasks ...
CU Independent

The Role of AI and Machine Learning in People Search Accuracy

See how AI and machine learning are transforming people search accuracy. Learn how ML improves precision and recall, powers ...
Scientific Research Publishing

Multimodal Digital Phenotyping for Bipolar Disorder: Robust Mood-State Classification and Early Relapse Risk Monitoring ()

Bipolar Disorder, Digital Phenotyping, Multimodal Learning, Face/Voice/Phone, Mood Classification, Relapse Prediction, T-SNE, Ablation Share and Cite: de Filippis, R. and Al Foysal, A. (2025) ...

Stony Brook University Develops Machine Learning Models that Predict PV System Underperformance on Heterogeneous Portfolios

With such increased predictive knowledge of solar systems, these anomaly detectors can significantly reduce costs of O&M, a major component of project economics in solar development. There is great ...
IEEE

Semi-Supervised Few-Shot Classification With Multitask Learning and Iterative Label Correction

Abstract: Few-shot learning enables rapid generalization from extremely limited training examples. While previous efforts have utilized meta-learning or data augmentation methods to mitigate the ...
IEEE

Safe Semi-Supervised Contrastive Learning Using In-Distribution Data as Positive Examples

Abstract: Semi-supervised learning (SSL) methods have shown promising results in solving many practical problems when only a few labels are available. The existing methods assume that the class ...