Recent advancements in machine learning have ushered in a transformative era for seismic data analysis. By integrating sophisticated algorithms such as convolutional neural networks (CNNs), generative ...

Data is fundamental to hydrological modeling and water resource management; however, it remains a major challenge in many ...

Machine learning is rapidly emerging as a pivotal tool in plant tissue culture research, offering innovative approaches to optimise protocols, predict morphogenic responses, and streamline ...

Electrocatalysis sits at the heart of clean hydrogen production, fuel cells, and carbon dioxide conversion, yet progress ...

Artificial Intelligence (AI) and Machine Learning (ML) are increasingly integral to database management, driving new levels of automation and intelligence in how data systems are administered. Modern ...

From fine-tuning open source models to building agentic frameworks on top of them, the open source world is ripe with ...

The Technical Psychoacoustics research group at the Aalto Acoustics Lab, within the Department of Information and Communications Engineering at Aalto University, invites applications for a one-year ...

A new artificial intelligence tool could aid in limiting or even prevent pandemics by identifying animal species that may harbor and spread viruses capable of infecting humans. The machine learning ...

Rules-based automation (RBA) and learning are two training mechanisms in robotics. While there are many others, these are two ...

The absence of reliable data on fundamental economic indicators (e.g. real GDP), combined with structural shifts in the economy, can severely constrain the ability to conduct accurate macroeconomic ...

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...

Researchers at Google have developed a new AI paradigm aimed at solving one of the biggest limitations in today’s large language models: their inability to learn or update their knowledge after ...