The hydrologic system is subjected unprecedented stresses and increasing demands driven by climate variabilities, landuse changes, groundwater ...

A new development in data science has given one popular machine learning tool an improved sense of place, enabling it to make ...

Autonomous AI post-training reached frontier scale for the first time: NVIDIA researchers published a paper showing an AI ...

Bigger has defined AI from day one. New data says task-specific small models beat frontier LLMs on accuracy, cost and speed — ...

Abstract: Cardiovascular disease (CVD) is the leading cause of death worldwide. A Machine Learning (ML) system can predict CVD in the early stages to mitigate mortality rates based on clinical data.

Hyperparameter optimization lies at the core of developing robust and reliable machine learning models. Unlike parameters learned during training, hyperparameters are set prior to the learning process ...

Cost-Effectiveness of Maintaining Higher Stem-Cell Collection Thresholds in the Chimeric Antigen Receptor T-Cell Era for Multiple Myeloma Predicting severe adverse events (SAEs) in oncology is ...

DeepHyper is first and foremost a hyperparameter optimization (HPO) library. By leveraging this core HPO functionnality, DeepHyper also provides neural architecture search, multi-fidelity and ensemble ...

This project implements state-of-the-art deep learning models for financial time series forecasting with a focus on uncertainty quantification. The system provides not just point predictions, but ...

ABSTRACT: This study presents a comprehensive and interpretable machine learning pipeline for predicting treatment resistance in psychiatric disorders using synthetically generated, multimodal data.