The project of phase's key role in complex and real NN

Last update: Nov 04, 2021

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Overview

Phase-in-NN

This is the code for our project at Princeton (co-authors: Yuqi Nie, Hui Yuan). The paper title is: "Neural Network is heterogeneous: Phase Matters More". To run the program you need to install tensorflow. Then you may activate your tensorflow environment and import MNIST as we have done here.

Mnist-complexNN-final.py: This is the code for complex NN. It has a single hidden layer with 100 nodes, and the back-propagtion is redesigned according to the appendix.

Mnist_realNN_multilayer-final.py: This is the code for real NN. It has two hidden layer with 512 and 100 nodes separately.

Owner

YuqiNie-lab

GitHub Repository

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The project of phase's key role in complex and real NN

Related tags

Overview

Phase-in-NN

Owner

YuqiNie-lab

Sequential GCN for Active Learning

Simple tools for logging and visualizing, loading and training

Official implementation for the paper: "Multi-label Classification with Partial Annotations using Class-aware Selective Loss"

Pytorch implementation for RelTransformer

we propose a novel deep network, named feature aggregation and refinement network (FARNet), for the automatic detection of anatomical landmarks.

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