TNLearn: An Open Source Python Package for Task-based Neurons
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Abstract (arXiv)
The brain does not rely on a single type of neuron to perform all kinds of tasks; instead, it designs different neurons for different tasks. The concept of task-based neurons represents a paradigm shift compared to task-based architectures. It argues that solving a specific problem requires customized neurons, as task-based neurons capture useful prior knowledge from task-related data. To facilitate the use of task-based neurons in scientific research and industrial applications, we introduce TNLearn, an open-source Python package that provides automated construction of task-based neurons and networks, enabling smooth training of task-based networks. Comprehensive documentation, including technical exposition, API reference, and representative examples, is available online. TNLearn is open-sourced at https://github.com/NewT123-WM/tnlearn and has become a PyTorch ecosystem project.
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References · 19
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7 more
- 2018On a Sparse Shortcut Topology of Artificial Neural Networkscited by 20
- 2017A New Type of Neurons for Machine Learningcited by 16
- 2017OpenML: An R Package to Connect to the Machine Learning Platform OpenMLcited by 12
- 2023One Neuron Saved Is One Neuron Earned: On Parametric Efficiency of Quadratic Networkscited by 6
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- 2024QuadraNet V2: Efficient and Sustainable Training of High-Order Neural Networks with Quadratic Adaptationcited by 3
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