Official Codes for Graph Modularity:Towards Understanding the Cross-Layer Transition of Feature Representations in Deep Neural Networks.

Last update: Dec 14, 2022

Overview

Dynamic-Graphs-Construction

Official Codes for Graph Modularity:Towards Understanding the Cross-Layer Transition of Feature Representations in Deep Neural Networks.

We give an example to understand the dynamic graphs: we leverage pretrained ResNet18 (Top1 acc: 94.78%) on CIFAR-10 to extract feature representations. Then we set N = 50, k = 3 for dynamic graphs construction. The result is shown in the gif below: Note that nodes of the same color represent samples of the same class. The darker the color of the edge, the higher the similarity between the two corresponding nodes. The modularity curve of this dynamic graph:

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Official Codes for Graph Modularity:Towards Understanding the Cross-Layer Transition of Feature Representations in Deep Neural Networks.

Related tags

Overview

Dynamic-Graphs-Construction

Owner

Code for paper "Document-Level Argument Extraction by Conditional Generation". NAACL 21'

Blind visual quality assessment on 360° Video based on progressive learning

Source code and Dataset creation for the paper "Neural Symbolic Regression That Scales"

Official implementation for (Show, Attend and Distill: Knowledge Distillation via Attention-based Feature Matching, AAAI-2021)

A task-agnostic vision-language architecture as a step towards General Purpose Vision

The project is an official implementation of our CVPR2019 paper "Deep High-Resolution Representation Learning for Human Pose Estimation"

Download from Onlyfans.com.

MDMM - Learning multi-domain multi-modality I2I translation

An executor that loads ONNX models and embeds documents using the ONNX runtime.

Use unsupervised and supervised learning to predict stocks

The implementation of PEMP in paper "Prior-Enhanced Few-Shot Segmentation with Meta-Prototypes"

phylotorch-bito is a package providing an interface to BITO for phylotorch

GANimation: Anatomically-aware Facial Animation from a Single Image (ECCV'18 Oral) [PyTorch]

Text-to-SQL in the Wild: A Naturally-Occurring Dataset Based on Stack Exchange Data

PyTorch implementation of paper A Fast Knowledge Distillation Framework for Visual Recognition.

Neuron class provides LNU (Linear Neural Unit), QNU (Quadratic Neural Unit), RBF (Radial Basis Function), MLP (Multi Layer Perceptron), MLP-ELM (Multi Layer Perceptron - Extreme Learning Machine) neurons learned with Gradient descent or LeLevenberg–Marquardt algorithm

WormMovementSimulation - 3D Simulation of Worm Body Movement with Neurons attached to its body

The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL), NeurIPS-2021

Code release for Universal Domain Adaptation(CVPR 2019)

Python Rapid Artificial Intelligence Ab Initio Molecular Dynamics