The device marks a major step forward in transforming how neuroscientists study the brain. By enabling high-resolution, real-time imaging of brain activity in freely moving mice, the miniaturized ...

An AI-driven digital-predistortion (DPD) framework can help overcome the challenges of signal distortion and energy ...

Altuna Akalin and his team at the Max Delbrück Center have developed a new tool to more precisely guide cancer treatment. Described in a paper published in “Nature Communications,” the tool, called ...

Bankruptcy prediction has traditionally relied on statistical approaches such as Altman’s Z-score, which use financial ratios ...

The integration of deep learning in biodiesel research accelerates feedstock evaluation and optimizes production, making it ...

1 Department of Qunli Ultrasound, The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China 2 Department of Ultrasound, Jilin Cancer Hospital, Changchun, Jilin, China ...

This study proposes a hybrid modeling approach that integrates a Physics Informed Neural Network (PINN) and a long short-term memory (LSTM) network to predict river water temperature in a defined ...

In Weeks 5-8, we'll deepen our understanding of neural networks by exploring various activation functions, optimization techniques, and advanced architecture components. The focus is on both the ...

Abstract: Deep Reinforcement Learning (DRL) enable several areas of artificial intelligence, including perception recognition, expert system, recommender program and game. Also, graph neural networks ...

Abstract: The Paper explores different aspects of deep learning techniques and neural networks in the fields of healthcare, time-series forecasting, agriculture, and other relevant sectors through ...