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

Qubic attempted a 51% attack on Monero while training its AI model AIGarth. It's now posting on social media—and the public ...

Geoffrey Hinton is sounding the alarm about the risks of artificial intelligence. He believes AI could become a superintelligent entity that might threaten humanity. Known as the "Godfather of AI," ...

Generalize Hopfield-like neural networks using a deformed maximum entropy principle. Exhibit explosive transitions, multi-stability, and memory capacity enhancements. Are analytically tractable via ...

Abstract: In the field of time series prediction, runoff prediction is a critical subfield. Accurate runoff forecasting is essential for optimizing water resource allocation and mitigating flood risks ...

As summer winds down, many of us in continental Europe are heading back north. The long return journeys from the beaches of southern France, Spain, and Italy once again clog alpine tunnels and ...

This repository contains a time series forecasting project using the Google Play Store dataset. It systematically compares RNN, LSTM, and GRU models, optimized via Keras Tuner, to predict future app ...

Abstract: Due to the numerous advantages of dual-band infrared radiation (DBIR) attitude measurement (AM) technology, it has garnered significant attention from industry and academia. However, ...

Introduction: Segmentation of echocardiograms plays a crucial role in clinical diagnosis. Beyond accuracy, a major challenge of video echocardiogram analysis is the temporal consistency of consecutive ...