Python Conditional-neural-process Resources

CoulombGas This code implements the neural canonical transformation approach to the thermodynamic properties of uniform electron gas. Building on JAX,

InfoNeRF: Ray Entropy Minimization for Few-Shot Neural Volume Rendering Pytorch implementation of our method for regularizing nerual radiance fields f

PYGON A Graph Neural Network Tool for Recovering Dense Sub-graphs in Random Dense Graphs. Installation This code requires to install and run the graph

MothPruning Scientific Overview Originally inspired by biological nervous systems, deep neural networks (DNNs) are powerful computational tools for mo

Classification of Long Sequential Data using Circular Dilated Convolutional Neural Networks arXiv preprint: https://arxiv.org/abs/2201.02143. Architec

Safe Control for Black-box Dynamical Systems via Neural Barrier Certificates Installation Clone the repository: git clone https://github.com/Zengyi-Qi

BERN2 We present BERN2 (Advanced Biomedical Entity Recognition and Normalization), a tool that improves the previous neural network-based NER tool by

DesktopTranslator Local cross-platform machine translation GUI, based on CTranslate2 Download Windows Installer You can either download a ready-made W

PythonPID_Tuner Step 1: Takes a Process Reaction Curve in csv format - assumes data at 100ms interval (column names CV and PV) Step 2: Makes a rough e

TensorLayer is a novel TensorFlow-based deep learning and reinforcement learning library designed for researchers and engineers. It provides an extens

Intro Real-time object detection and classification. Paper: version 1, version 2. Read more about YOLO (in darknet) and download weight files here. In

dev-setup Motivation Setting up a new developer machine can be an ad-hoc, manual, and time-consuming process. dev-setup aims to simplify the process w

Natural Language Processing with PyTorch Build Intelligent Language Applications Using Deep Learning By Delip Rao and Brian McMahan Welcome. This is a

NLP-Models-Tensorflow, Gathers machine learning and tensorflow deep learning models for NLP problems, code simplify inside Jupyter Notebooks 100%. Tab

🎉TensorFlow2.0-Examples🎉! "Talk is cheap, show me the code." ----- Linus Torvalds Created by YunYang1994 This tutorial was designed for easily divin

Anime4K Anime4K is a set of open-source, high-quality real-time anime upscaling/denoising algorithms that can be implemented in any programming langua

Minimal ML algorithms This repo includes minimal implementations of popular ML algorithms using pure python and numpy. The purpose of these notebooks

DCS-Net This is the implementation of "DCS-Net: Deep Complex Subtractive Neural Network for Monaural Speech Enhancement" Steps to run the model Edit V

Fast Training of Neural Lumigraph Representations using Meta Learning Project Page | Paper | Data Alexander W. Bergman, Petr Kellnhofer, Gordon Wetzst

This is the official implementation of our neural-network-based fast diffuse room impulse response generator (FAST-RIR) for generating room impulse responses (RIRs) for a given acoustic environment.

Haxaw-Chess Haxaw: Haxaw is the Neural Network based chess engine made with Python and Tensorflow/Keras. Also uses the python-chess library. (WIP: Imp

VarCnn: The Deep Learning Powered VAR

simple_pytorch_example project is a toy example of a python script that instantiates and trains a PyTorch neural network on the FashionMNIST dataset

A Simple Neural Network from scratch A Simple Neural Network from scratch in Pyt

LSTM Neural Network for Time Series Prediction LSTM built using the Keras Python package to predict time series steps and sequences. Includes sine wav

Deep Learning for Time Series Classification As the simplest type of time series data, univariate time series provides a reasonably good starting poin

Deep Learning for Time Series Classification This is the companion repository for our paper titled "Deep learning for time series classification: a re

Multilabel time series classification with LSTM Tensorflow implementation of model discussed in the following paper: Learning to Diagnose with LSTM Re

Deep learning for time series forecasting Flow forecast is an open-source deep learning for time series forecasting framework. It provides all the lat

Distilling-the-Knowledge-in-a-Neural-Network This is an implementation of a part of the paper "Distilling the Knowledge in a Neural Network" (https://

Overcoming-Catastrophic-forgetting-in-Neural-Networks Elastic weight consolidation technique for incremental learning. About Use this API if you dont

REMIND Your Neural Network to Prevent Catastrophic Forgetting This is a PyTorch implementation of the REMIND algorithm from our ECCV-2020 paper. An ar

Python Outlier Detection (PyOD) Deployment & Documentation & Stats & License PyOD is a comprehensive and scalable Python toolkit for detecting outlyin

WTTE-RNN Weibull Time To Event Recurrent Neural Network A less hacky machine-learning framework for churn- and time to event prediction. Forecasting p

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Distilling-the-knowledge-in-neural-network Teaches a student network from the knowledge obtained via training of a larger teacher network This is an i

Brain-Inspired Replay A PyTorch implementation of the continual learning experiments with deep neural networks described in the following paper: Brain

Analyzed the data of Visa applicants, built a predictive model to facilitate the process of visa approvals, and based on important factors that significantly influence the Visa status recommended a suitable profile for the applicants for whom the visa should be certified or denied.

Cherche (search in French) allows you to create a neural search pipeline using retrievers and pre-trained language models as rankers. Cherche is meant to be used with small to medium sized corpora. Cherche's main strength is its ability to build diverse and end-to-end pipelines.

REQUIREMENTS Linux Docker Python/bash set up image "docker build -t game ." create db container "run my_whatever/game_docker/pdb create" # creating po

The CodeSearchNet challenge has been concluded We would like to thank all participants for their submissions and we hope that this challenge provided

Creative Applications of Deep Learning w/ Tensorflow This repository contains lecture transcripts and homework assignments as Jupyter Notebooks for th

Deep Learning Time Series Forecasting List of state of the art papers focus on deep learning and resources, code and experiments using deep learning f

Knet Knet (pronounced "kay-net") is the Koç University deep learning framework implemented in Julia by Deniz Yuret and collaborators. It supports GPU

Open nsfw model This repo contains code for running Not Suitable for Work (NSFW) classification deep neural network Caffe models. Please refer our blo

NLP Tutorial A list of NLP(Natural Language Processing) tutorials built on PyTorch. Table of Contents A step-by-step tutorial on how to implement and

Π-NAS This repository provides the evaluation code of our submitted paper: Pi-NAS: Improving Neural Architecture Search by Reducing Supernet Training

Skeletal-GNN Code for "Learning Skeletal Graph Neural Networks for Hard 3D Pose Estimation" ICCV'21 Various deep learning techniques have been propose

Spatio-Temporal Dynamic Inference Network for Group Activity Recognition The source codes for ICCV2021 Paper: Spatio-Temporal Dynamic Inference Networ

duralava duralava is a neural network which can simulate a lava lamp in an infinite loop. Example This is not a real lava lamp but a "fake" one genera

Django CMS Project for quicksetup with minimal installation process.

BERN2 We present BERN2 (Advanced Biomedical Entity Recognition and Normalization

Documentation | Paper [JMLR] | Tutorials | Benchmarks | Examples DIG: Dive into Graphs is a turnkey library for graph deep learning research. Why DIG?

NNR and global probabilities estimation and analysis in peptides or protein fragments This module calculates global and NNR conformation dependent pro

August 16, 2021: Version 5 has been released. Read about the changes in version 5, or read the full documentation. Version 5 is for Python 3.8+ only.

neural_network_for_stock_price_prediction Neural networks for stock price predic

Neural Networks Demystified Supporting iPython notebooks for the YouTube Series Neural Networks Demystified. I've included formulas, code, and the tex

Machine Learning Study 혼자 해보기 기여자 (Contributors) ✨ Teddy Lee 🏠 HongJaeKwon 🏠 Seungwoo Han 🏠 Tae Heon Kim 🏠 Steve Kwon 🏠 SW Song 🏠 K1A2 🏠 Wooil

The Lovász-Softmax loss: A tractable surrogate for the optimization of the intersection-over-union measure in neural networks Maxim Berman, Amal Ranne

Advbox is a toolbox to generate adversarial examples that fool neural networks in PaddlePaddle、PyTorch、Caffe2、MxNet、Keras、TensorFlow and Advbox can benchmark the robustness of machine learning models. Advbox give a command line tool to generate adversarial examples with Zero-Coding.

Mish: Self Regularized Non-Monotonic Activation Function BMVC 2020 (Official Paper) Notes: (Click to expand) A considerably faster version based on CU

Bayesian Neural Networks Pytorch implementations for the following approximate inference methods: Bayes by Backprop Bayes by Backprop + Local Reparame

One Pixel Attack How simple is it to cause a deep neural network to misclassify an image if an attacker is only allowed to modify the color of one pix

ILearnDeepLearning.py Description People say that nothing develops and teaches you like getting your hands dirty. This repository contains small proje

READ THE DOCUMENTATION CONTRIBUTING A general-purpose encoder-decoder framework for Tensorflow that can be used for Machine Translation, Text Summariz

#NeuralTalk Warning: Deprecated. Hi there, this code is now quite old and inefficient, and now deprecated. I am leaving it on Github for educational p

AlexNet training on ImageNet LSVRC 2012 This repository contains an implementation of AlexNet convolutional neural network and its training and testin

Convolutional Neural Networks for Sentence Classification Code for the paper Convolutional Neural Networks for Sentence Classification (EMNLP 2014). R

Multi-level Disentanglement Graph Neural Network (MD-GNN) This is a PyTorch implementation of the MD-GNN, and the code includes the following modules:

CSDI This is the github repository for the NeurIPS 2021 paper "CSDI: Conditional Score-based Diffusion Models for Probabilistic Time Series Imputation

Image-Classification CIFAR-10 Photo Classification CIFAR-10_Dataset_Classfication CIFAR-10 Photo Classification Dataset CIFAR is an acronym that stand

Getting Started This tutorial is designed to get you started with Algorand devel

Headliner Demo This is a demo showcasing our Headliner package. In particular, we trained a simple seq2seq model on an English-German dataset. We didn

Image 🖼 Classification App Boilerplate Have you been puzzled by tons of videos, blogs and other resources on the internet and don't know where and ho

Music_Gen_Streamlit "Music Generation using Neural Networks" Streamlit App TO DO: Make a run_app.sh Introduction [~5 min] (Sohaib) Team Member names/i

DGMS This is the code of the paper "Finding the Task-Optimal Low-Bit Sub-Distribution in Deep Neural Networks". Installation Our code works with Pytho

Introduction Codebase for the paper Transformer Embeddings of Irregularly Spaced Events and Their Participants. This codebase contains two packages: a

DCT based fast weights This repository contains the official code for the paper: Training and Generating Neural Networks in Compressed Weight Space. T

GNEE - GAT Neural Event Embeddings This repository contains source code for the GNEE (GAT Neural Event Embeddings) method introduced in the paper: "Se

TripClick Baselines with Improved Training Data Welcome 🙌 to the hub-repo of our paper: Establishing Strong Baselines for TripClick Health Retrieval

cluster-link-prediction This repository provides some of the code implemented and the data used for the work proposed in "A Cluster-Based Trip Predict

CV Backbones including GhostNet, TinyNet, TNT (Transformer in Transformer) developed by Huawei Noah's Ark Lab. GhostNet Code TinyNet Code TNT Code Pyr

Neural Wireframe Renderer: Learning Wireframe to Image Translations Pytorch implementation of ideas from the paper Neural Wireframe Renderer: Learning

STEFANN: Scene Text Editor using Font Adaptive Neural Network @ The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2020.

GAN Compression project | paper | videos | slides [NEW!] GAN Compression is accepted by T-PAMI! We released our T-PAMI version in the arXiv v4! [NEW!]

NICE-GAN-pytorch - Official PyTorch implementation of NICE-GAN: Reusing Discriminators for Encoding: Towards Unsupervised Image-to-Image Translation

DeepSIM: Image Shape Manipulation from a Single Augmented Training Sample (ICCV 2021 Oral) Project | Paper Official PyTorch implementation of the pape

MatchGAN: A Self-supervised Semi-supervised Conditional Generative Adversarial Network This repository is the official implementation of MatchGAN: A S

Net2Net Code accompanying the NeurIPS 2020 oral paper Network-to-Network Translation with Conditional Invertible Neural Networks Robin Rombach*, Patri

Fashion-Entity-Classification - Fashion-MNIST is a dataset of Zalando's article images—consisting of a training set of 60,000 examples and a test set of 10,000 examples. Each example is a 28x28 grayscale image, associated with a label from 10 classes. Zalando intends Fashion-MNIST to serve as a direct drop-in replacement for the original MNIST dataset for benchmarking machine learning algorithms. It shares the same image size and structure of training and testing splits.

autoencoder Implementation of the Reducing the Dimensionality of Data with Neural Network – G. E. Hinton and R. R. Salakhutdinov paper. Notes Aim to m

How transferable are features in deep neural networks? This repository contains source code necessary to reproduce the results presented in the follow

Deep Learning - Image Captioning with Convolutional and Recurrent Neural Nets ========================================================================

Introduction This neural system for image captioning is roughly based on the paper "Show, Attend and Tell: Neural Image Caption Generation with Visual

Neural Machine Translation (seq2seq) Tutorial Authors: Thang Luong, Eugene Brevdo, Rui Zhao (Google Research Blogpost, Github) This version of the tut

Computer-Vision-Paper-Reviews Computer Vision Paper Reviews with Key Summary along Papers & Codes. Jonathan Choi 2021 50+ Papers across Computer Visio

SimpleDepthEstimation Introduction This is an unified codebase for NN-based monocular depth estimation methods, the framework is based on detectron2 (

Scene-Change-Detection - A video scene detection algorithm is designed to detect a variety of different scenes within a video. There is a very simple definition for a scene: It is a series of logically and chronologically related shots taken in a specific order to depict an over-arching concept or story.

LSTM based Sentiment Classification using Tensorflow - Amazon Reviews Rating (Dataset) The dataset is from Amazon Review Data (2018)

BasicNeuralNetwork - This project looks over the basic structure of a neural network and how machine learning training algorithms work. For this project, I used the sigmoid function as an activation function along with stochastic gradient descent to adjust the weights and biases.