horrible-dong/DNRT
[ICLR 2024] Dynamic Neural Response Tuning
This project offers a new way to design Artificial Neural Networks (ANNs) that can better differentiate between categories of input data. It takes standard ANN architectures and improves their ability to learn by adjusting how they process information based on the input signal. The result is a more accurate and robust neural network, which is useful for machine learning engineers and researchers building advanced AI models.
Use this if you are a machine learning researcher or practitioner looking to enhance the performance and interpretability of your neural networks across various classification and recognition tasks.
Not ideal if you are looking for a plug-and-play solution for data analysis without prior experience in deep learning model development.
Stars
16
Forks
2
Language
Python
License
Apache-2.0
Category
Last pushed
Nov 26, 2025
Commits (30d)
0
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