robertsdionne/neural-network-papers
A categorized bibliography and reading list of neural network and deep learning papers and resources.
Not currently ranked — collecting fresh signals.
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This repository is an organized awesome list curating links to papers, books, datasets, pretrained models, and research across neural network subtopics. It spans convolutional networks, recurrent networks, reinforcement learning, adversarial networks, autoencoders, biologically plausible learning, training innovations, and related hardware and cognitive architecture research.
Frequently asked
- What is robertsdionne/neural-network-papers?
- A categorized bibliography and reading list of neural network and deep learning papers and resources.
- Is neural-network-papers open source?
- Yes — robertsdionne/neural-network-papers is an open-source project tracked on heatdrop.
- What language is neural-network-papers written in?
- robertsdionne/neural-network-papers is primarily written in JavaScript.
- How popular is neural-network-papers?
- robertsdionne/neural-network-papers has 2k stars on GitHub.
- Where can I find neural-network-papers?
- robertsdionne/neural-network-papers is on GitHub at https://github.com/robertsdionne/neural-network-papers.