Dynamic neural network architectures systematically adjust their internal configuration at inference time to balance computational cost against predictive performance. Rather than executing every ...

Dynamic Graph Neural Networks (Dynamic GNNs) have emerged as powerful tools for modeling real-world networks with evolving topologies and node attributes over time. A survey by Professors Zhewei Wei, ...

A key objective of several neuroscience studies is to understand and model how the dynamics of distinct populations of neurons give rise to specific human and animal behaviors. Many existing methods ...

NJU and PKU researchers combine physical modeling with neural representation to enable high-resolution dynamic scene ...

Scientists in Spain have used genetic algorithms to optimize a feedforward artificial neural network for the prediction of energy generation of PV systems. Genetic algorithms use “parents” and ...