CownowAn/DiffusionNAG
Official PyTorch implementation of "DiffusionNAG: Predictor-guided Neural Architecture Generation with Diffusion Models" (ICLR 2024)
This project helps machine learning researchers and practitioners automatically design neural network architectures that are optimized for specific tasks. You input your desired dataset (like image classification or object detection data) and receive a highly performant neural network architecture tailored to your objectives. It significantly reduces the time and computational resources typically spent exploring countless network configurations, making AI model development more efficient.
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Use this if you are developing AI models and want to efficiently discover optimal neural network architectures without extensive manual searching or trial-and-error.
Not ideal if you are looking for a simple, off-the-shelf model to apply directly without engaging in architecture design or model optimization research.
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43
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8
Language
Python
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Last pushed
Mar 20, 2024
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