Python Artficial-neural-network Resources

PyOpenVINO - An Experimental Python Implementation of OpenVINO Inference Engine (minimum-set) Description The PyOpenVINO is a spin-off product from my

Multi-view graph embedding clustering network: Joint self-supervision and block diagonal representation Simple implementation of our paper MVGC. The d

DiffGAN-TTS - PyTorch Implementation PyTorch implementation of DiffGAN-TTS: High

Neural Machine Translation Framework: PyTorch Repository contaning my implementa

Dark Finix - Hacking Framework. Dark Finix is a all in one hacking framework wit

SatelliteNeRF PyTorch-based Neural Radiance Fields adapted to satellite domain.

A Network-Based High-Level Data Classification Algorithm Using Betweenness Centr

DIGAN (ICLR 2022) Official PyTorch implementation of "Generating Videos with Dyn

S2S2Net Sentinel-2 Super-Resolution Segmentation Network Getting started Install

A Contrastive Framework for Neural Text Generation Authors: Yixuan Su, Tian Lan,

HashNeRF-pytorch Instant-NGP recently introduced a Multi-resolution Hash Encodin

Towards Adversarial Robustness of Bayesian Neural Network through Hierarchical V

Point-NeRF: Point-based Neural Radiance Fields Project Sites | Paper | Primary c

Efficient Guided Evolution for Neural Architecture Search Usage Create a conda e

PINN(s): Physics-Informed Neural Network(s) for von Karman vortex street This is

Kompressor Branch CI Coverage main (active) main development A neural compression framework built on top of JAX. Install setup.py assumes a compatible

A small, UNOFFICIAL module to communicate with Triller's API. I plan to add more features/methods in the future.

TensorFlow2-GAN Collection of tf2.0 implementations of Generative Adversarial Network varieties presented in research papers. Model architectures will

B2EA: An Evolutionary Algorithm Assisted by Two Bayesian Optimization Modules for Neural Architecture Search This is the offical implementation of the

AllSet This is the repo for our paper: You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks. We prepared all codes and a subse

TTS-GAN: A Transformer-based Time-Series Generative Adversarial Network This repository contains code from the paper "TTS-GAN: A Transformer-based Tim

TGIN Tensorflow implementation of our method: "Triangle Graph Interest Network for Click-through Rate Prediction". Files in the folder dataset/ electr

MarkovGNN This is the official PyTorch-Geometric implementation of MarkovGNN paper under the title "MarkovGNN: Graph Neural Networks on Markov Diffusi

TorchMD-net TorchMD-Net provides state-of-the-art graph neural networks and equivariant transformer neural networks potentials for learning molecular

LyaNet: A Lyapunov Framework for Training Neural ODEs Provide the model type--config-name to train and test models configured as those shown in the pa

Transfer-Learning-in-Reinforcement-Learning Transfer Reinforcement Learning for Differing Action Spaces via Q-Network Representations Final Report Tra

Diffrax Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. Diffrax is a JAX-based library providing numerical differe

OMLT is a Python package for representing machine learning models (neural networks and gradient-boosted trees) within the Pyomo optimization environment.

C-CNN: Contourlet Convolutional Neural Networks This repo implemenets the Contourlet-CNN as described in C-CNN: Contourlet Convolutional Neural Networ

MoCap-Solver is a data-driven-based robust marker denoising method, which takes raw mocap markers as input and outputs corresponding clean markers and skeleton motions.

EquiBind: geometric deep learning for fast predictions of the 3D structure in which a small molecule binds to a protein

FILM: Frame Interpolation for Large Scene Motion Project | Paper | YouTube | Benchmark Scores Tensorflow 2 implementation of our high quality frame in

Julia package for contraction of tensor networks, based on the sweep line algorithm outlined in the paper General tensor network decoding of 2D Pauli codes

Code for CCA-SSG model proposed in the NeurIPS 2021 paper From Canonical Correlation Analysis to Self-supervised Graph Neural Networks.

HGCN The official repo of "HGCN: Harmonic Gated Compensation Network For Speech Enhancement", which was accepted at ICASSP2022. How to use step1: Calc

This paper proposes a novel differentiable architecture search method by formulating it into a distribution learning problem. We treat the continuously relaxed architecture mixing weight as random variables, modeled by Dirichlet distribution.

One-Shot Neural Ensemble Architecture Search by Diversity-Guided Search Space Shrinking This is an official implementation for NEAS presented in CVPR

CATE: Computation-aware Neural Architecture Encoding with Transformers Code for paper: CATE: Computation-aware Neural Architecture Encoding with Trans

Awesome AutoDL A curated list of automated deep learning related resources. Inspired by awesome-deep-vision, awesome-adversarial-machine-learning, awe

Convolutional Neural Network to detect deforestation in the Amazon Rainforest This project is part of my final work as an Aerospace Engineering studen

PyTorch NeRF and pixelNeRF NeRF: Tiny NeRF: pixelNeRF: This repository contains minimal PyTorch implementations of the NeRF model described in "NeRF:

Price Prediction model is used to develop an LSTM model to predict the future market price of Bitcoin and Ethereum.

The project has set itself the goal of analyzing the thoughts and interaction of Italian users through the social posts expressed through the Twitter platform on the day of the entry into force of the new measures. In particular, we want to research the reference hubs present on the network, but also the sentiment and emotions of peoples with respect to the new limitations.

UMPNet: Universal Manipulation Policy Network for Articulated Objects Zhenjia Xu, Zhanpeng He, Shuran Song Columbia University Robotics and Automation

Disclaimer This tool is for Educational purpose only. We do not promote or encourage any illegal activities. Summary These are Simple python scripts t

PacketPy About PacketPy is an open-source solution for stress testing network devices using different testing methods. Currently, there are only two c

Energy_Output_Predictor Artificial Neural network regression model to predict the energy output in a combined cycle power plant. Abstract Energy outpu

This project is a PyTorch implementation of Neural Radiance Fields (NeRF) for reproduction of results whilst running at a faster speed.

Create a semantic search engine with a neural network (i.e. BERT) whose knowledge base can be updated. This engine can later be used for downstream tasks in NLP such as Q&A, summarization, generation, and natural language understanding (NLU).

PyZebrascope - an open-source Python platform for brain-wide neural activity imaging in behaving zebrafish

A tool to get a minimalist view of any architecture This tool has only be tested with the models included in this repo. Therefore, I can't guarantee t

Multi-Stage Spatial-Temporal Convolutional Neural Network (MS-GCN) This code implements the skeleton-based action segmentation MS-GCN model from Autom

SBINN: Systems-biology informed neural network The source code for the paper M. Daneker, Z. Zhang, G. E. Karniadakis, & L. Lu. Systems biology: Identi

This package requires jax, tensorflow, and numpy. Either tensorflow or scikit-learn can be used for loading data. To run in a nix-shell with required

TONet Introduction The official implementation of "TONet: Tone-Octave Network for Singing Melody Extraction from Polyphonic Music", in ICASSP 2022 We

Introduction This repository is for Deep Learning agent of Starcraft2. It is very similar to AlphaStar of DeepMind except size of network. I only test

A mini-scale reproduction code of the AlphaStar program. Note: the original AlphaStar is the AI proposed by DeepMind to play StarCraft II.

FewBit FewBit — a library for memory efficient training of large neural networks. Its efficiency originates from storage optimizations applied to back

ES_OTN_Public Carlos Güemes Palau, Paul Almasan, Pere Barlet Ros, Albert Cabellos Aparicio Contact us: [email protected], contactus@bn

DNA sequence classification by Deep Neural Network: Project Overview worked on the DNA sequence classification problem where the input is the DNA sequ

RegNet Pytorch Implementation of "Desigining Network Design Spaces", Radosavovic et al. CVPR 2020. Paper | Official Implementation RegNet offer a very

CAP-Classification-CRNN A deep learning model based on Inception modules paired with gated recurrent units (GRU) for the classification of CAP phases

Phase diagram of Stochastic Gradient Descent in high-dimensional two-layer neural networks Under construction. Description Code for Phase diagram of S

MinkLoc++: Lidar and Monocular Image Fusion for Place Recognition Paper: MinkLoc++: Lidar and Monocular Image Fusion for Place Recognition accepted fo

N-HiTS: Neural Hierarchical Interpolation for Time Series Forecasting Recent progress in neural forecasting instigated significant improvements in the

DiffStride is a pooling layer with learnable strides. Unlike strided convolutions, average pooling or max-pooling that require cross-validating stride values at each layer, DiffStride can be initialized with an arbitrary value at each layer (e.g. (2, 2) and during training its strides will be optimized for the task at hand.

Semantic-NeRF: Semantic Neural Radiance Fields Project Page | Video | Paper | Data In-Place Scene Labelling and Understanding with Implicit Scene Repr

TDY-CNN for Text-Independent Speaker Verification Official implementation of Temporal Dynamic Convolutional Neural Network for Text-Independent Speake

Siren: Implicit Neural Representations with Periodic Activation Functions The unofficial Tensorflow 2 implementation of the paper Implicit Neural Repr

This is a python based command line Network Scanner utility, which input as an argument for the exact IP address or the relative IP Address range you wish to do the Network Scan for and returns all the available IP addresses with their MAC addresses on your current Network.

NeuralForecast is a Python library for time series forecasting with deep learning models. It includes benchmark datasets, data-loading utilities, evaluation functions, statistical tests, univariate model benchmarks and SOTA models implemented in PyTorch and PyTorchLightning.

Anonymously Reverse shell over Tor Network using Hidden Services without portfortwarding Tor ağı ile Dark Web servislerini kullanarak anonim biçimde p

Network tests automation Network tests automation About this repository Requirements Requirements on your laptop Requirements on the switches Quick te

Recovering-Brain-Structure-Network-Using-Functional-Connectivity Framework: Papers: This repository provides a PyTorch implementation of the models ad

Detect and Classify Brain Tumor using CNN. A system performing detection and classification by using Deep Learning Algorithms using Convolution-Neural Network (CNN).

ssnt-loss ℹ️ This is a WIP project. the implementation is still being tested. A pure PyTorch implementation of the loss described in "Online Segment t

Classification using Deep Learning Requirements PyTorch version = 1.9.1+cu111 Python version = 3.8.10 PyTorch-Lightning version = 1.4.9 Huggingface

Python project that aims to discover CDP neighbors and map their Layer-2 topology within a shareable medium like Visio or Draw.io.

This repository contains the official PyTorch implementation of the "CRF-RNN" semantic image segmentation method, published in the ICCV 2015

This project is a web porting for NVlabs' StyleGAN2, to facilitate exploring all kinds characteristic of StyleGAN networks. Thanks for NVlabs' excelle

AvatarGAN ✨ Generate Cartoon Images using DC-GAN Deep Convolutional GAN is a generative adversarial network architecture. It uses a couple of guidelin

pixel_character_generator Generating retro pixel game characters with Generative Adversarial Networks. Dataset "TinyHero" included. Dataset TinyHero D

The unified machine learning framework, enabling framework-agnostic functions, layers and libraries. Contents Overview In a Nutshell Where Next? Overv

keras-semantic-segmentation-example Example of semantic segmentation in Keras Single class example: Generated data: random ellipse with random color o

RuCLIPtiny Zero-shot image classification model for Russian language RuCLIP tiny (Russian Contrastive Language–Image Pretraining) is a neural network

This is a model made out of Neural Network specifically a Convolutional Neural Network model. This was done with a pre-built dataset from the tensorflow and keras packages. There are other alternative libraries that can be used for this purpose, one of which is the PyTorch library.

Python Assignments for the Deep Learning lectures by Andrew NG on coursera with complete submission for grading capability.

This project is a convolutional neural network (CNN) that analyzes self-generated images in a variety of languages to find etymological similarities. Specifically, the goal is to prove that computer vision can be used to identify cognates known to exist, and perhaps lead linguists to evidence of unknown cognates.

IPScanner 🔬 A simple threaded IP-Scanner written in python3 that can monitor lo

Iterative refinement graph neural network for antibody sequence-structure co-des

neural-modular Simple codebase for flexible neural net training. Allows for seamless exchange of models, dataset, and optimizers. Uses hydra for confi

Equivariant Subgraph Aggregation Networks (ESAN) This repository contains the official code of the paper Equivariant Subgraph Aggregation Networks (IC

traiNNer traiNNer is an open source image and video restoration (super-resolution, denoising, deblurring and others) and image to image translation to

CAMPARI: Camera-Aware Decomposed Generative Neural Radiance Fields Paper | Supplementary | Video | Poster If you find our code or paper useful, please

DIR-GNN "Discovering Invariant Rationales for Graph Neural Networks" (ICLR 2022)

Contrastive Learning for Neural Topic Model This repository contains the impleme

World-Happiness-Report We are going to visualise what are the factors and which

Random Forest classifier for neural subtypes extracted from extracellular recordings from human brain organoids.

Cite our paper if you find this project useful https://www.ijariit.com/manuscripts/v7i4/V7I4-1139.pdf Abstract Image processing technology is used in

Our product DrLeaf which not only makes the work easier but also reduces the effort and expenditure of the farmer to identify the disease and its treatment methods. We have to upload the image of an affected plant’s leaf through our website and our plant disease prediction model predicts and returns the disease name. And along with the disease name, we also provide the best suitable methods to cure the disease.