Adaptive Neural

Adaptive neural networks (ANNs) are a class of neural networks designed to adjust their structure or parameters during or after training, improving efficiency and robustness. Current research focuses on enhancing ANN performance in noisy environments, adapting to varying computational resources (e.g., edge devices), and improving their energy efficiency. These advancements are impacting diverse fields, including medical diagnosis (e.g., improved disease detection), robotics (e.g., brain-computer interfaces), and scientific computing (e.g., solving differential equations), by enabling more efficient and reliable solutions to complex problems.