The framework predicts how proteins will function with several interacting mutations and finds combinations that work well together.
Researchers from the Department of Computer Science at Bar-Ilan University and from NVIDIA's AI research center in Israel ...
In a new study published in Physical Review Letters, researchers used machine learning to discover multiple new classes of ...
WiMi Releases Hybrid Quantum-Classical Neural Network (H-QNN) Technology for Efficient MNIST Binary Image Classification ...
Background: Stress-induced hyperglycemia (SHG) represents a significant metabolic complication in non-diabetic cardiac surgery older adult patients, with substantial implications for postoperative ...
ABSTRACT: Artificial deep neural networks (ADNNs) have become a cornerstone of modern machine learning, but they are not immune to challenges. One of the most significant problems plaguing ADNNs is ...
Abstract: In this article, we utilize the concept of average controllability in graphs, along with a novel rank encoding method, to enhance the performance of Graph Neural Networks (GNNs) in social ...
High-precision GNSS applications, such as real-time displacement monitoring and vehicle navigation, rely heavily on resolving carrier-phase ambiguities. However, traditional methods like the R-ratio ...
Understanding and preventing drug side effects holds a profound influence on drug development and utilization, profoundly impacting patients’ physical and mental well-being. Traditional artificial ...
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