IEEE

Enhancing Explainability of Neural Networks Through Architecture Constraints

Abstract: Prediction accuracy and model explainability are the two most important objectives when developing machine learning algorithms to solve real-world problems. Neural networks are known to ...
note

[Manifolds and Deep Learning] It is interesting to view backpropagation from the perspective of differential geometry

Why does the gradient propagate in the "reverse" direction? Backpropagation can be understood using only the chain rule from high school mathematics. However, the concepts of differential geometry are ...
IEEE

Yiqi Liu

Root Mean Square Error,Long Short-term Memory,Neural Network,Attention Mechanism,Model Predictive Control,Recurrent Neural Network,Control Input,Convolutional Neural Network,Deep Learning,Model ...
GitHub

network.py

simple, easily readable, and easily modifiable. It is not optimized, and omits many desirable features.
GitHub

Quantization and Synthesis (Device Specific Code Generation) for ADI's MAX78000 and MAX78002 Edge AI Devices

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