Python Neural-ranking Resources

BioPy is a collection (in-progress) of biologically-inspired algorithms written in Python. Some of the algorithms included are mor

nn_builder lets you build neural networks with less boilerplate code. You specify the type of network you want and it builds it. Install pip install n

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

Peek-a-Boo: What (More) is Disguised in a Randomly Weighted Neural Network, and How to Find It Efficiently This repository is the official implementat

Google AI Open Images - Object Detection Track: Open Solution This is an open solution to the Google AI Open Images - Object Detection Track 😃 More c

Airbus Ship Detection Challenge This is an open solution to the Airbus Ship Detection Challenge. Our goals We are building entirely open solution to t

Official Pytorch implementation of ICLR 22 paper Fast Differentiable Matrix Square Root

Deep-Learning-Project This Deep Learning Model Predicts that from which disease you are suffering. This Project Covers the Topics of Deep Learning Int

Neural Machine Translation (NMT) tutorial with OpenNMT-py. Data preprocessing, model training, evaluation, and deployment.

GNES is Generic Neural Elastic Search, a cloud-native semantic search system based on deep neural network.

Grover is a model for Neural Fake News -- both generation and detection. However, it probably can also be used for other generation tasks.

GalaXC GalaXC: Graph Neural Networks with Labelwise Attention for Extreme Classification @InProceedings{Saini21, author = {Saini, D. and Jain,

Handheld Multi-Frame Neural Depth Refinement This is the official code repository for the work: The Implicit Values of A Good Hand Shake: Handheld Mul

Efficient Online Bayesian Inference for Neural Bandits By Gerardo Durán-Martín, Aleyna Kara, and Kevin Murphy AISTATS 2022.

Biomedical Entity Linking This repo provides the code for the paper BERT might be Overkill: A Tiny but Effective Biomedical Entity Linker based on Res

Deep_Learning & Neural_Network_Lab 实验环境 Python 3.9 Anaconda3(官网下载或清华镜像都行) PyTorch 1.10.1(安装代码如下) conda install pytorch torchvision torchaudio cudatool

Code to reproduce the results for Statistically Robust Neural Network Classification, published in UAI 2021

MarcoEngine Marco Engine - interesnaya neyronnaya shakhmatnaya set', kotoraya ispol'zuyet metod samoobucheniya(dostizheniye khoroshoy igy putem proboy

TCNN Pandey A, Wang D L. TCNN: Temporal convolutional neural network for real-time speech enhancement in the time domain[C]//ICASSP 2019-2019 IEEE Int

Neural Net Image Classifier Employs neural networks to classify images into four categories: ship, automobile, dog or frog Viterbi_1.py uses a classic

🧠 Text-2-Cellular Automata Using Neural Cellular Automata + OpenAI CLIP (Work in progress) Examples Text Prompt: Cthulu is watching cthulu_is_watchin

Brain-Tumor-Detection A convolutional neural network model built with Tensorflow & Keras to detect brain tumor and its different variants. Data of the

Mixed neural likelihood estimation for models of decision-making Mixed neural likelihood estimation (MNLE) enables Bayesian parameter inference for mo

this is a simple artificial neural network model using deep learning and torch-audio to classify cats and dog sounds.

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

This repository contains the implementation for the paper: No-Reference Image Quality Assessment via Transformers, Relative Ranking, and Self-Consiste

EfficientWord-Net Hotword detection based on one-shot learning Home assistants require special phrases called hotwords to get activated (eg:"ok google

SAPE Project page Paper Official implementation for the paper "SAPE: Spatially-Adaptive Progressive Encoding for Neural Optimization". Environment Cre

Instant Neural Graphics Primitives Ever wanted to train a NeRF model of a fox in under 5 seconds? Or fly around a scene captured from photos of a fact

This is the implementation of "Training deep neural networks via direct loss minimization" published at ICML 2016 in PyTorch. The implementation targe

DeepMIH: Deep Invertible Network for Multiple Image Hiding (TPAMI 2022) This repo is the official code for DeepMIH: Deep Invertible Network for Multip

Evolving Neural Networks in JAX This repository holds code displaying techniques for applying evolutionary network training strategies in JAX. Each sc

Unet_erythema_detection A basic neural network for image segmentation. 前期准备 1.在logs文件夹中下载h5权重文件，百度网盘链接在logs文件夹中 2.将所有原图 放置在“/dataset_1/JPEGImages/”文件夹

Prediction of MBA refinance Index (Mortgage prepayment) Deep Neural Network based Model The ability to predict mortgage prepayment is of critical use

FairEdit Relevent Publication FairEdit: Preserving Fairness in Graph Neural Networks through Greedy Graph Editing

ContinualPassageRanking Repository for the paper "Continual Learning of Long Topic Sequences in Neural Information Retrieval". In this repository you

JAX Models Table of Contents About The Project Getting Started Prerequisites Installation Usage Contributing License Contact About The Project The JAX

Authors Marcus Lenler Garsdal, [email protected] Valdemar Søgaard, [email protected] Simon Moe Sørensen, [email protected] Introduction This repo contains the

Accurate Phylogenetic Inference with a Symmetry-preserving Neural Network Model Claudia Solis-Lemus Shengwen Yang Leonardo Zepeda-Núñez This repositor

Source codes for Improved Few-Shot Visual Classification (CVPR 2020), Enhancing Few-Shot Image Classification with Unlabelled Examples (WACV 2022) and Beyond Simple Meta-Learning: Multi-Purpose Models for Multi-Domain, Active and Continual Few-Shot Learning (TPAMI 2022 - in submission)

1 MAGNN This repo is the official implementation for Multi-Scale Adaptive Graph Neural Network for Multivariate Time Series Forecasting. 1.1 The frame

Neural-Koopman-Lyapunov-Control Code for our paper: Neural Koopman Lyapunov Control Requirements dReal4: v4.19.02.1 PyTorch: 1.2.0 The learning framew

Awesome Deep Learning Table of Contents Books Courses Videos and Lectures Papers Tutorials Researchers Websites Datasets Conferences Frameworks Tools

DeepAmandine This is an artificial intelligence based on GPT-3 that you can chat with, it is very nice and makes a lot of jokes. We wish you a good ex

Real Time Object Recognition From your Screen Desktop . In this post, I will explain how to build a simply program to detect objects from you desktop

FusionNet_Pytorch FusionNet: A deep fully residual convolutional neural network for image segmentation in connectomics Requirements Pytorch 0.1.11 Pyt

TransferNet: Learning Transferrable Knowledge for Semantic Segmentation with Deep Convolutional Neural Network Created by Seunghoon Hong, Junhyuk Oh,

Neural-Network-Basics Aim of this Repository: From Perceptron model to Deep Neural Network (from scratch) in Python. ** Currently working on a basic N

Weakly Supervised Segmentation with TensorFlow This repo contains a TensorFlow implementation of weakly supervised instance segmentation as described

Part Detector Discovery This is the code used in our paper "Part Detector Discovery in Deep Convolutional Neural Networks" by Marcel Simon, Erik Rodne

Film review classification Решение задачи классификации отзывов на фильмы на положительные и отрицательные с помощью рекуррентных нейронных сетей 1. З

Neural Residual Flow Fields for Efficient Video Representations 1. Download MPI

Cryptocurrency Prediction with Artificial Intelligence (Deep Learning via LSTM Neural Networks)- Emirhan BULUT

Use stochastic processes to generate samples and use them to train a fully-connected neural network based on Keras which will then be used to generate residuals

Food recognition model using convolutional neural network & computer vision. The goal is to match or beat the DeepFood Research Paper

Simple implementation of Equivariant GNN A short implementation of E(n) Equivariant Graph Neural Networks for HOMO energy prediction. Just 50 lines of

Primeira_Rede_Neural_Convolucional Rede Neural Convolucional feita durante o processo seletivo do Laboratório de Inteligência Artificial da FACOM (UFM

ff-neural-network A Python module for the generation and training of an entry-level feedforward neural network. This repository serves as a repurposin

Volume Rendering of Neural Implicit Surfaces Project Page | Paper | Data This re

Table of Contents Introduction Installation Examples Pre-trained models Quick start using colab JARVIS-ALIGNN webapp Peformances on a few datasets Use

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

NeROIC: Neural Object Capture and Rendering from Online Image Collections This repository is for the source code for the paper NeROIC: Neural Object C

merlot_reserve Code release for "MERLOT Reserve: Neural Script Knowledge through Vision and Language and Sound" MERLOT Reserve (in submission) is a mo

ReceptiveFieldAnalysisToolbox This is RFA-Toolbox, a simple and easy-to-use library that allows you to optimize your neural network architectures usin

Intel® Neural Compressor targeting to provide unified APIs for network compression technologies, such as low precision quantization, sparsity, pruning, knowledge distillation, across different deep learning frameworks to pursue optimal inference performance.

Are you looking for X-as-service? Try the Cloud-Native Neural Search Framework for Any Kind of Data bert-as-service Using BERT model as a sentence enc

This repository has gone stale as I unfortunately do not have the time to maintain it anymore. If you would like to continue the development of it as

YoloV3 Implemented in TensorFlow 2.0 This repo provides a clean implementation of YoloV3 in TensorFlow 2.0 using all the best practices. Key Features

Python Machine Learning Jupyter Notebooks (ML website) Dr. Tirthajyoti Sarkar, Fremont, California (Please feel free to connect on LinkedIn here) Also

Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.

candl A tiny, pedagogical implementation of a neural network library with a pytorch-like API. The primary use of this library is for education. Use th

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

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

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