Efficiency What are the future directions in developing more sophisticated memory architectures for neural networks

Neural Networks, pp. 271–280. RESEARCH IN PROGRESS. • “Seller-Provided Information and Return Policies for Experience Goods,” under review at. Decision ... Dec 19, 2019 ... Abstract: Attribution methods provide insights into the decision-making of machine learning models like artificial neural networks. We do so by performing experiments on artificial neural networks in the context of fairness in machine learning, where the goal is to induce fairness in the ... Jun 23, 2020 ... In this paper we develop a novel mathematical formalism for the modeling of neural information networks endowed with additional structure. Feb 22, 2023 ... We compare this control to a regularly-trained neural network, and show that perturbations on nodes carrying relay information cause failures in ... Data-driven network performance prediction for B5G networks: a graph neural network approach. Yaqoob, M., Trestian, R. and Nguyen, H. 2022. Data-driven ... information carried by the network via neural codes. 1.3. Consciousness and Informational Complexity. The idea of computational mod- els of consciousness ... Feb 6, 2025 ... Abstract and Figures. While there is much knowledge about local neuronal circuitry, considerably less is known about how neuronal input is ... Jun 29, 2018 ... The brain has numerous levels of interaction ranging from gene networks that control cell function to neural circuits that control behavior. Klinkner, K.L., Shalizi, C.R., Camperi, M.F. Measuring shared information and coordinated activity in neuronal networks (2005). Advances in Neural Information ...