Nature

Transfer Learning with Kernel Methods

Transfer learning refers to the process of adapting a model trained on a source task to a target task. While kernel methods are conceptually and computationally simple models that are competitive on a ...
Nature

Robust evaluation of deep learning-based representation methods for survival and gene essentiality prediction on bulk RNA-seq data

Deep learning (DL) has shown potential to provide powerful representations of bulk RNA-seq data in cancer research. However, there is no consensus regarding the impact of design choices of DL ...
Frontiers

Numerical foundations for scalable statistical and machine learning methods

Across modern data-intensive disciplines, the union of numerical computation, statistics, and machine learning has become ...
Frontiers

Advancing Machine Learning for Space Weather Forecasting: Integrating Solar Observations, Geomagnetic Storm Prediction, and GNSS Ionospheric Forecasting

Space weather forecasting remains a major challenge in heliophysics, as geomagnetic storms continue to pose significant risks to satellite operations, power ...
BMJ Open

Use of case-based, problem-based and team-based learning in public health education – a scoping review

Objectives Active learning strategies, including case-based learning (CBL), problem-based learning (PBL) and team-based ...
pharmaphorum

Agile learning focused on driving change: Lessons for Centre of Excellence leaders

The Stem research and interviews with senior Centre of Excellence (CoE) leaders at Boehringer Ingelheim, Takeda, Merck, Novo ...