Python Conditional-neural-process Resources

Awesome Artificial Intelligence, Machine Learning and Deep Learning as we learn it. Study notes and a curated list of awesome resources of such topics.

AutoML for Text, Image, and Tabular Data AutoGluon automates machine learning tasks enabling you to easily achieve strong predictive performance in yo

imagededup is a python package that simplifies the task of finding exact and near duplicates in an image collection.

NanoDet-Plus⚡Super fast and lightweight anchor-free object detection model. 🔥Only 980 KB(int8) / 1.8MB (fp16) and run 97FPS on cellphone🔥

Please read the blog post that goes with this code! Jupyter Notebook Setup System Requirements: Python, pip (Optional) virtualenv To start the Jupyter

GANs in Action by Jakub Langr and Vladimir Bok List of available code: Chapter 2: Colab, Notebook Chapter 3: Notebook Chapter 4: Notebook Chapter 6: C

Coursera-deep-learning-specialization - Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models

PyTorch-Style-Transfer This repo provides PyTorch Implementation of MSG-Net (ours) and Neural Style (Gatys et al. CVPR 2016), which has been included

Speech Emotion Analyzer The idea behind creating this project was to build a machine learning model that could detect emotions from the speech we have

Hyperparameter Optimization of Machine Learning Algorithms This code provides a hyper-parameter optimization implementation for machine learning algor

nerf_pl Update: an improved NSFF implementation to handle dynamic scene is open! Update: NeRF-W (NeRF in the Wild) implementation is added to nerfw br

TensorFlow 101: Introduction to Deep Learning I have worked all my life in Machine Learning, and I've never seen one algorithm knock over its benchmar

Saliency Methods 🔴 Now framework-agnostic! (Example core notebook) 🔴 🔗 For further explanation of the methods and more examples of the resulting ma

What is Detectron2-FC Detectron2-FC a fast construction platform of neural network algorithm based on detectron2. We have been working hard in two dir

PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation Created by Charles R. Qi, Hao Su, Kaichun Mo, Leonidas J. Guibas from Sta

neural image analogies This is basically an implementation of this "Image Analogies" paper, In our case, we use feature maps from VGG16. The patch mat

Tensorflow Project Template A simple and well designed structure is essential for any Deep Learning project, so after a lot of practice and contributi

Art041_NN_Feed_Forward Public repository containing materials used for Feed Forward (FF) Neural Networks article. -- Illustration of a very simple Fee

Simple-Neural-Network From Scratch in Python This is a simple Neural Network created without any Machine Learning Libraries. The only dependencies are

Taxonomizing local versus global structure in neural network loss landscapes Int

Cancer-and-Tumor-Detection-Using-Inception-model In this repo i am gonna show you how i did cancer/tumor detection in lungs using deep neural networks

BRNet code for "Automated assessment of BI-RADS categories for ultrasound images using multi-scale neural networks with an order-constrained loss func

youtube_dl_helper A helper program meant to automate the process of downloading mp3 files from YouTube using youtube-dl library Dependencies In order

CS5242_2021 Neural Networks and Deep Learning, NUS CS5242, 2021 Cloud Machine #1 : Google Colab (Free GPU) Follow this Notebook installation : https:/

TennisBusinessIntelligenceProject - A project consists in a set of assignements corresponding to a BI process: data integration, construction of an OLAP cube, qurying of a OPLAP cube and reporting.

Siamese Deep Neural Networks for Semantic Text Similarity PyTorch A repository c

PPL Quantization Tool(PPL 量化工具) PPL Quantization Tool (PPQ) is a powerful offlin

Hyperopt for solving CIFAR-100 with a convolutional neural network (CNN) built with Keras and TensorFlow, GPU backend This project acts as both a tuto

Self Governing Neural Networks (SGNN): the Projection Layer A SGNN's word projections preprocessing pipeline in scikit-learn In this notebook, we'll u

Neural Fractal Create Fractals Using Complex-Valued Neural Networks! Home Page Features Define Dynamical Systems Using Complex-Valued Neural Networks

pytorch-minimal-gaussian-process In search of truth, simplicity is needed. There exist heavy-weighted libraries, but as you know, we need to go bare b

Easily train or fine-tune SOTA computer vision models from one training repository. SuperGradients Introduction Welcome to SuperGradients, a free open

Neural Machine Translation communication system The model is basically direct to convert one source language to another targeted language using encode

Neural View Synthesis and Matching for Semi-Supervised Few-Shot Learning of 3D Pose Release Notes The official PyTorch implementation of Neural View S

Self-Training for Neural Sequence Generation This repo includes instructions for running noisy self-training algorithms from the following paper: Revi

Sequence labeler This is a neural network sequence labeling system. Given a sequence of tokens, it will learn to assign labels to each token. Can be u

Neural Structured Learning in TensorFlow Neural Structured Learning (NSL) is a new learning paradigm to train neural networks by leveraging structured

SemiNAS: Semi-Supervised Neural Architecture Search This repository contains the code used for Semi-Supervised Neural Architecture Search, by Renqian

Graph Contrastive Learning with Augmentations PyTorch implementation for Graph Contrastive Learning with Augmentations [poster] [appendix] Yuning You*

Img-process-manual - Opencv Library basic graphic processing algorithm coding reproduction based on Numpy and Matplotlib library

DeepCreamPy Decensoring Hentai with Deep Neural Networks. Formerly named DeepMindBreak. A deep learning-based tool to automatically replace censored a

A simplistic and efficient pure-python neural network library from Phys Whiz with CPU and GPU support.

GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training Original implementation for paper GCC: Graph Contrastive Coding for Graph Neural N

SelfGNN A PyTorch implementation of "SelfGNN: Self-supervised Graph Neural Networks without explicit negative sampling" paper, which will appear in Th

Pretraining on Dynamic Graph Neural Networks Our article is PT-DGNN and the code is modified based on GPT-GNN Requirements python 3.6 Ubuntu 18.04.5 L

DGI Deep Graph Infomax (Veličković et al., ICLR 2019): https://arxiv.org/abs/1809.10341 Overview Here we provide an implementation of Deep Graph Infom

Graph-InfoClust-GIC [PAKDD 2021] PAKDD'21 version Graph InfoClust: Maximizing Coarse-Grain Mutual Information in Graphs Preprint version Graph InfoClu

ncnn ncnn is a high-performance neural network inference computing framework optimized for mobile platforms. ncnn is deeply considerate about deployme

No-Transaction Band Network: A Neural Network Architecture for Efficient Deep Hedging Minimal implementation and experiments of "No-Transaction Band N

Numerical Bric-a-Brac Collections of numerical techniques with Python and standard computational packages (Numpy, SciPy, Numba, Matplotlib ...). Diffe

Lunar Lunar is a neural network aimbot that uses real-time object detection accelerated with CUDA on Nvidia GPUs. About Lunar can be modified to work

On Adversarial Robustness: A Neural Architecture Search perspective Preparation: Clone the repository: https://github.com/tdchaitanya/nas-robustness.g

Py_PSNODE General neural ODE and DAE modules for power system dynamic modeling. The PyTorch-based ODE solver is developed based on torchdiffeq. Sample

Block Modeling-Guided Graph Convolutional Neural Networks This repository contains the demo code of the paper: Block Modeling-Guided Graph Convolution

The implementation of Parameter Differentiation based Multilingual Neural Machine Translation .

InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization Authors: Fan-yun Sun, Jordan Hoffm

SUGAR Code for "SUGAR: Subgraph Neural Network with Reinforcement Pooling and Self-Supervised Mutual Information Mechanism" Overview train.py: the cor

NeoDTI NeoDTI: Neural integration of neighbor information from a heterogeneous network for discovering new drug-target interactions (Bioinformatics).

SelfTask-GNN A PyTorch implementation of "Self-supervised Learning on Graphs: Deep Insights and New Directions". [paper] In this paper, we first deepe

Pretrain-Recsys This is our Tensorflow implementation for our WSDM 2021 paper: Bowen Hao, Jing Zhang, Hongzhi Yin, Cuiping Li, Hong Chen. Pre-Training

SLAPS-GNN This repo contains the implementation of the model proposed in SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks

GPT-GNN: Generative Pre-Training of Graph Neural Networks GPT-GNN is a pre-training framework to initialize GNNs by generative pre-training. It can be

Self-supervised Auxiliary Learning with Meta-paths for Heterogeneous Graphs This repository is the implementation of SELAR. Dasol Hwang* , Jinyoung Pa

Self-supervised edge features for improved Graph Neural Network training Data availability: Here is a link to the raw data for the organoids dataset.

DrRepair: Learning to Repair Programs from Error Messages This repo provides the source code & data of our paper: Graph-based, Self-Supervised Program

Official PyTorch implementation of the paper: "Self-Supervised Relational Reasoning for Representation Learning" (2020), Patacchiola, M., and Storkey,

The implementation of Parameter Differentiation based Multilingual Neural Machin

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

Automatic-Notion-Backup A script to automate the process of downloading Markdown and CSV backups of Notion. In addition, the data is processed to remo

Mycodo Environmental Regulation System Latest version: 8.12.9 Mycodo is open source software for the Raspberry Pi that couples inputs and outputs in i

Embeddings Embeddings is a python package that provides pretrained word embeddings for natural language processing and machine learning. Instead of lo

Easily Extendable Basic Deep Metric Learning Pipeline Karsten Roth ([email protected]), Biagio Brattoli ([email protected]) When using thi

Memory-Efficient Multi-Level In-Situ Generation (MLG) By Jiaqi Gu, Hanqing Zhu, Chenghao Feng, Mingjie Liu, Zixuan Jiang, Ray T. Chen and David Z. Pan

Characterizing possible failure modes in physics-informed neural networks This repository contains the PyTorch source code for the experiments in the

jumpdiff jumpdiff is a python library with non-parametric Nadaraya─Watson estimators to extract the parameters of jump-diffusion processes. With jumpd

HinetPy is a Python package to simplify tedious data request, download and format conversion tasks related to NIED Hi-net. NIED Hi-net | Source Code |

Pyfood is a simple Python package to process food, in different languages. Pyfood's ambition is to be the go-to library to deal with food, recipes, on

RCDNet: A Model-driven Deep Neural Network for Single Image Rain Removal (CVPR2020) Hong Wang, Qi Xie, Qian Zhao, and Deyu Meng [PDF] [Supplementary M

Version 3.3.5 — release candidate Introduction FloPy includes support for MODFLOW 6, MODFLOW-2005, MODFLOW-NWT, MODFLOW-USG, and MODFLOW-2000. Other s

This codebase is being actively maintained, please create and issue if you have issues using it Basics All data files are included under losses and ea

Neural Chess It's not the best chess engine, but it is a chess engine. Proof of concept neural network chess engine (feed-forward multi-layer perceptr

A Python library that tees the standard output & standard error from the current process to files on disk, while preserving terminal semantics (so breakpoint(), etc work as normal)

The neural architecture of language: Integrative modeling converges on predictive processing Code accompanying the paper The neural architecture of la

DHAP Source code of SIGIR2021 Long Paper: One Chatbot Per Person: Creating Personalized Chatbots based on Implicit User Profiles . Preinstallation Fir

NeLF: Neural Light-transport Field for Single Portrait View Synthesis and Relighting Official PyTorch Implementation of paper "NeLF: Neural Light-tran

tfgraphviz tfgraphviz is a module to visualize a TensorFlow's data flow graph like TensorBoard using Graphviz. tfgraphviz enables to provide a visuali

Logo by Zhuoning Yuan LibAUC: A Machine Learning Library for AUC Optimization Website | Updates | Installation | Tutorial | Research | Github LibAUC a

ttslearn: Library for Pythonで学ぶ音声合成 (Text-to-speech with Python) 日本語は以下に続きます (Japanese follows) English: This book is written in Japanese and primaril

PolyBot A tool to help the Poly copy-reading process! :D Let's face it-computers are better are repeatitive tasks. And, in spite of what one may want

Upload files or folders (even with subfolders) to Amazon S3 in a totally automatized way taking advantage of: Amazon S3 Multipart Upload: The uploaded

BPMN_RPA Robotic Process Automation in Windows and Linux by using BPMN diagrams. With this Framework you can draw Business Process Model Notation base

Neural Enhance Example #1 — Old Station: view comparison in 24-bit HD, original photo CC-BY-SA @siv-athens. As seen on TV! What if you could increase

NeRF Minimal Jax implementation of NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis. Result of Tiny-NeRF RGB Depth

Evolving Search Space for Neural Architecture Search Usage Install all required dependencies in requirements.txt and replace all ..path/..to in the co

NeLF: Neural Light-transport Field for Single Portrait View Synthesis and Relighting Official PyTorch Implementation of paper "NeLF: Neural Light-tran

Breaking the Curse of Space Explosion: Towards Effcient NAS with Curriculum Search Pytorch implementation for "Breaking the Curse of Space Explosion:

MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks This is the code for the paper: MentorNet: Learning Data-Driven Curriculum fo

AdaptationSeg This is the Python reference implementation of AdaptionSeg proposed in "Curriculum Domain Adaptation for Semantic Segmentation of Urban

PythonPID_Simulator Python PID Controller and Process Simulator (FOPDT) with GUI. Run the File. Then select Model Values and Tune PID.. Hit Refresh to

Population Shift Monitoring popmon is a package that allows one to check the stability of a dataset. popmon works with both pandas and spark datasets.