Disaster Response

Data-driven network performance prediction for B5G networks: a graph neural network approach. Yaqoob, M., Trestian, R. and Nguyen, H. 2022. Data-driven ... Aug 30, 2023 ... To explore this topic, we used an in vitro neural network of cortical neurons that was trained to play a simplified game of 'Pong' to ... a type of universal function approximators that can embed the knowledge of any physical laws that govern a given data-set in the learning process. Sep 1, 2021 ... We find that specialized neuronal populations in auditory cortex form functional networks during auditory task performance whose structures depend on both ... Jun 29, 2022 ... Neural Networks are one particular type of Machine Learning technique. They are a type of artificial intelligence modeled on the brain. Dec 19, 2019 ... Abstract: Attribution methods provide insights into the decision-making of machine learning models like artificial neural networks. information carried by the network via neural codes. 1.3. Consciousness and Informational Complexity. The idea of computational mod- els of consciousness ... ... information theory in the evaluation of single neuron responses and neural networks. The question of the neural code has been debated heatedly since the ... Nov 9, 2018 ... You don't lose a few neural connections and with it 80% of your consciousness. The richness of our stream of experience is stable across small ... Neural networks integrating information and primary reward. Early neuroscience studies of information seeking in monkeys focused on the “reward prediction error ...