Frontiers

Machine Learning for Mining Plant Functional Genes

Plants are constantly exposed to a wide array of biotic and abiotic stresses in their natural environments, posing ...

AI develops easily understandable solutions for unusual experiments in quantum physics

Researchers at the University of Tuebingen, working with an international team, have developed an artificial intelligence that designs entirely new, sometimes unusual, experiments in quantum physics ...
IEEE

Hybrid Transformer-KAN Within Federated Learning Framework: A Novel Machine Learning Approach for Improved Short-Term Weather Forecasting

Abstract: Among the various methods used for time series prediction tasks in weather forecasting, Transformer can effectively extract global information and has achieved tremendous success. However, ...
TMCnet

Data Normalization vs. Standardization: What's the Difference and When to Use Each

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and ...
玩具人

T-SPARK SYNERGENEX "EVA Prime Unit-01": The Dream Machine Born from the Powerful Collaboration of Transformers and Evangelion!

Japan's TAKARA TOMY toy company's high-end toy brand T-SPARK, known for its "SYNERGENEX" dream transforming toy series that collaborates with popular IPs, has officially announced an amazing new work ...
Utrecht University

Olifant – An efficient, explainable, and eco-friendly approach to Large Language Modeling

In this online lecture and accompanying demo, Antal van den Bosch will demonstrate Olifant, a recently revived language model that offers an energy-efficient alternative to Large Language Models (LLMs ...
IEEE

sQUlearn: A Python Library for Quantum Machine Learning [Focus: Quantum Software and Its Engineering]

Abstract: sQUlearn introduces a user-friendly, noisy intermediate-scale quantum (NISQ)-ready Python library for quantum machine learning (QML), designed for seamless integration with classical machine ...