A toolbox for receptive field analysis and visualizing neural network architectures
Channel Optimization for Convolutional Neural Networks [ICCV2021]
Efficient Auto-Channel Size Optimization for CNNs [ICMLA2021]
A deep learning system that automatically designs optimal CNN architectures using Neural Architecture Search to classify lung - colon cancer from histopathology images. Achieves 99.72% accuracy across five cancer types with robust regularization. PyTorch-based solution ready for medical imaging deployment with exceptional generalization performane
Testing submission of AWS batch jobs using BoTorch (via Ax) and TorchX for neural architecture search
Tensorflow2 implementation of "Neural Architecture Search"
Two population GA for concurrent optimization of feed-forward NN learnable and meta-parameters. Effectively an optimizer alternative to gradient descent based loosely on cooperative co-evolution methodology.
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