A collection of 100 Deep Learning images and visualizations

Overview

Deep Learning visuals

A collection of Deep Learning images and visualizations. The project has been developed by the AI Summer team and currently contains almost 100 images.

This repository was inspired by:

The images have been created using https://www.diagrams.net/ over the past years.

Contents

Can I use them?

Of course. You are allowed to use the images anywhere you like ( even for commercial use), as long as you attribute AI Summer.

Examples

Vision Transformer

Inception block

Layer normalization

Graph convolution

Owner
AI Summer
Learn Deep Learning and Artificial Intelligence. Discord server: https://discord.gg/k6NXwe7PXh
AI Summer
Official codes: Self-Supervised Learning by Estimating Twin Class Distribution

TWIST: Self-Supervised Learning by Estimating Twin Class Distributions Codes and pretrained models for TWIST: @article{wang2021self, title={Self-Sup

Bytedance Inc. 85 Dec 15, 2022
Data reduction pipeline for KOALA on the AAT.

KOALA KOALA, the Kilofibre Optical AAT Lenslet Array, is a wide-field, high efficiency, integral field unit used by the AAOmega spectrograph on the 3.

4 Sep 26, 2022
ML-Ensemble – high performance ensemble learning

A Python library for high performance ensemble learning ML-Ensemble combines a Scikit-learn high-level API with a low-level computational graph framew

Sebastian Flennerhag 764 Dec 31, 2022
Little tool in python to watch anime from the terminal (the better way to watch anime)

ani-cli Script working again :), thanks to the fork by Dink4n for the alternative approach to by pass the captcha on gogoanime A cli to browse and wat

Harshith 4.5k Dec 31, 2022
Multiple style transfer via variational autoencoder

ST-VAE Multiple style transfer via variational autoencoder By Zhi-Song Liu, Vicky Kalogeiton and Marie-Paule Cani This repo only provides simple testi

13 Oct 29, 2022
R-package accompanying the paper "Dynamic Factor Model for Functional Time Series: Identification, Estimation, and Prediction"

dffm The goal of dffm is to provide functionality to apply the methods developed in the paper “Dynamic Factor Model for Functional Time Series: Identi

Sven Otto 3 Dec 09, 2022
A Deep Learning Framework for Neural Derivative Hedging

NNHedge NNHedge is a PyTorch based framework for Neural Derivative Hedging. The following repository was implemented to ease the experiments of our pa

GUIJIN SON 17 Nov 14, 2022
This repo is for segmentation of T2 hyp regions in gliomas.

T2-Hyp-Segmentor This repo is for segmentation of T2 hyp regions in gliomas. By downloading the model from here you can use it to segment your T2w ima

1 Jan 18, 2022
The Fundamental Clustering Problems Suite (FCPS) summaries 54 state-of-the-art clustering algorithms, common cluster challenges and estimations of the number of clusters as well as the testing for cluster tendency.

FCPS Fundamental Clustering Problems Suite The package provides over sixty state-of-the-art clustering algorithms for unsupervised machine learning pu

9 Nov 27, 2022
An implementation of paper `Real-time Convolutional Neural Networks for Emotion and Gender Classification` with PaddlePaddle.

简介 通过PaddlePaddle框架复现了论文 Real-time Convolutional Neural Networks for Emotion and Gender Classification 中提出的两个模型,分别是SimpleCNN和MiniXception。利用 imdb_crop

8 Mar 11, 2022
Implement A3C for Mujoco gym envs

pytorch-a3c-mujoco Disclaimer: my implementation right now is unstable (you ca refer to the learning curve below), I'm not sure if it's my problems. A

Andrew 70 Dec 12, 2022
Understanding the Generalization Benefit of Model Invariance from a Data Perspective

Understanding the Generalization Benefit of Model Invariance from a Data Perspective This is the code for our NeurIPS2021 paper "Understanding the Gen

1 Jan 15, 2022
With this package, you can generate mixed-integer linear programming (MIP) models of trained artificial neural networks (ANNs) using the rectified linear unit (ReLU) activation function

With this package, you can generate mixed-integer linear programming (MIP) models of trained artificial neural networks (ANNs) using the rectified linear unit (ReLU) activation function. At the momen

ChemEngAI 40 Dec 27, 2022
Code accompanying paper: Meta-Learning to Improve Pre-Training

Meta-Learning to Improve Pre-Training This folder contains code to run experiments in the paper Meta-Learning to Improve Pre-Training, NeurIPS 2021. P

28 Dec 31, 2022
Replication of Pix2Seq with Pretrained Model

Pretrained-Pix2Seq We provide the pre-trained model of Pix2Seq. This version contains new data augmentation. The model is trained for 300 epochs and c

peng gao 51 Nov 22, 2022
A light weight data augmentation tool for training CNNs and Viola Jones detectors

hey-daug A light weight data augmentation tool for training CNNs and Viola Jones detectors (Haar Cascades). This tool inflates your data by up to six

Jaiyam Sharma 2 Nov 23, 2019
Experiments for Fake News explainability project

fake-news-explainability Experiments for fake news explainability project This repository only contains the notebooks used to train the models and eva

Lorenzo Flores (Lj) 1 Dec 03, 2022
Auto-Encoding Score Distribution Regression for Action Quality Assessment

DAE-AQA It is an open source program reference to paper Auto-Encoding Score Distribution Regression for Action Quality Assessment. 1.Introduction DAE

13 Nov 16, 2022
The original weights of some Caffe models, ported to PyTorch.

pytorch-caffe-models This repo contains the original weights of some Caffe models, ported to PyTorch. Currently there are: GoogLeNet (Going Deeper wit

Katherine Crowson 9 Nov 04, 2022
A object detecting neural network powered by the yolo architecture and leveraging the PyTorch framework and associated libraries.

Yolo-Powered-Detector A object detecting neural network powered by the yolo architecture and leveraging the PyTorch framework and associated libraries

Luke Wilson 1 Dec 03, 2021