Research articleFull text access. Rapid learning of spatial representations for goal-directed navigation based on a novel model of hippocampal place fields.
Bibliographic content of Neural Networks, Volume 161.
Jun 6, 2022 · This paper presents a computationally feasible method to compute rigorous bounds on the interval-generalisation of regression analysis.
Jun 5, 2021 · Journal reference: Neural Networks Volume 161, April 2023, Pages 598-613. Related DOI : https://doi.org/10.1016/j.neunet.2023.02.013. Focus to ...
Bibliographic content of Neural Networks.
Graph Neural Networks (GNNs) are deep learning methods which provide the ... Neural Networks Volume 161, Issue C. Apr 2023. 778 pages. ISSN:0893-6080.
Convolutional neural networks (CNNs) are often described as promising models of human vision, yet they show many differences from human abilities.
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Infinite width limits of deep neural networks often have tractable forms. They have been used to analyse the behaviour of finite networks, as well as being ...
(2021). Improving Uncertainty Calibration of Deep Neural Networks via Truth Discovery and Geometric Optimization. Proceedings of Machine Learning Research, 161, ...
Reinforcement learning policies based on deep neural networks are vulnerable to imperceptible adversarial perturbations to their inputs.