Towards brain-inspired artificial intelligence

M Poo - National Science Review, 2018 - academic.oup.com
A wave of artificial intelligence (AI) has swept across the globe. The World Artificial
Intelligence Conference 2018, held in Shanghai this September, drew thousands of …

[HTML][HTML] Computational foundations of natural intelligence

M Van Gerven - Frontiers in computational neuroscience, 2017 - frontiersin.org
New developments in AI and neuroscience are revitalizing the quest to understanding
natural intelligence, offering insight about how to equip machines with human-like …

Intriguing properties of neural networks

C Szegedy, W Zaremba, I Sutskever, J Bruna… - arXiv preprint arXiv …, 2013 - arxiv.org
Deep neural networks are highly expressive models that have recently achieved state of the
art performance on speech and visual recognition tasks. While their expressiveness is the …

[图书][B] Inside deep learning: Math, algorithms, models

E Raff - 2022 - books.google.com
Journey through the theory and practice of modern deep learning, and apply innovative
techniques to solve everyday data problems. In Inside Deep Learning, you will learn how to …

Limited correspondence in visual representation between the human brain and convolutional neural networks

Y Xu, M Vaziri-Pashkam - BioRxiv, 2020 - biorxiv.org
Convolutional neural networks (CNNs) have achieved very high object categorization
performance recently. It has increasingly become a common practice in human fMRI …

Neural network models and deep learning

N Kriegeskorte, T Golan - Current Biology, 2019 - cell.com
Originally inspired by neurobiology, deep neural network models have become a powerful
tool of machine learning and artificial intelligence. They can approximate functions and …

Cognitive computing and neural networks: Reverse engineering the brain

AS Maida - Handbook of Statistics, 2016 - Elsevier
Cognitive computing seeks to build applications which model and mimic human thinking.
One approach toward achieving this goal is to develop brain-inspired computational models …

Comparing the visual representations and performance of humans and deep neural networks

RA Jacobs, CJ Bates - Current Directions in Psychological …, 2019 - journals.sagepub.com
Although deep neural networks (DNNs) are state-of-the-art artificial intelligence systems, it is
unclear what insights, if any, they provide about human intelligence. We address this issue …

Deep learning: our miraculous year 1990-1991

J Schmidhuber - arXiv preprint arXiv:2005.05744, 2020 - arxiv.org
In 2020-2021, we celebrated that many of the basic ideas behind the deep learning
revolution were published three decades ago within fewer than 12 months in our" Annus …

Theoretical Insights into Neural Networks and Deep Learning: Advancing Understanding, Interpretability, and Generalization

UA Usmani, MU Usmani - 2023 World Conference on …, 2023 - ieeexplore.ieee.org
This work aims to provide profound insights into neural networks and deep learning,
focusing on their functioning, interpretability, and generalization capabilities. It explores …