2615 Repositories
Python neural-network-quantum-states Libraries
[CVPR 2022] Official code for the paper: "A Stitch in Time Saves Nine: A Train-Time Regularizing Loss for Improved Neural Network Calibration"
MDCA Calibration This is the official PyTorch implementation for the paper: "A Stitch in Time Saves Nine: A Train-Time Regularizing Loss for Improved
Repository for "Improving evidential deep learning via multi-task learning," published in AAAI2022
Improving evidential deep learning via multi task learning It is a repository of AAAI2022 paper, “Improving evidential deep learning via multi-task le
On Size-Oriented Long-Tailed Graph Classification of Graph Neural Networks
On Size-Oriented Long-Tailed Graph Classification of Graph Neural Networks We provide the code (in PyTorch) and datasets for our paper "On Size-Orient
Extensive Python3 network scanner, simplified.
Snake Map Extensive Python3 network scanner, simplified. _,.--. --..,_ .'`__ o `;__, `'.'. .'.'` '---'` '
Exploring the Dual-task Correlation for Pose Guided Person Image Generation
Dual-task Pose Transformer Network The source code for our paper "Exploring Dual-task Correlation for Pose Guided Person Image Generation“ (CVPR2022)
Learning the Beauty in Songs: Neural Singing Voice Beautifier; ACL 2022 (Main conference); Official code
Learning the Beauty in Songs: Neural Singing Voice Beautifier Jinglin Liu, Chengxi Li, Yi Ren, Zhiying Zhu, Zhou Zhao Zhejiang University ACL 2022 Mai
Experimental Python implementation of OpenVINO Inference Engine (very slow, limited functionality). All codes are written in Python. Easy to read and modify.
PyOpenVINO - An Experimental Python Implementation of OpenVINO Inference Engine (minimum-set) Description The PyOpenVINO is a spin-off product from my
The Begin button and menu for the Meadows operating system. The start button for UNIX/Linux.
By: Seanpm2001, Meadows Et; Al. Top README.md Read this article in a different language Sorted by: A-Z Sorting options unavailable ( af Afrikaans Afri
Tensorflow 1.13.X implementation for our NN paper: Wei Xia, Sen Wang, Ming Yang, Quanxue Gao, Jungong Han, Xinbo Gao: Multi-view graph embedding clustering network: Joint self-supervision and block diagonal representation. Neural Networks 145: 1-9 (2022)
Multi-view graph embedding clustering network: Joint self-supervision and block diagonal representation Simple implementation of our paper MVGC. The d
PyTorch Implementation of DiffGAN-TTS: High-Fidelity and Efficient Text-to-Speech with Denoising Diffusion GANs
DiffGAN-TTS - PyTorch Implementation PyTorch implementation of DiffGAN-TTS: High
Neural-Machine-Translation - Implementation of revolutionary machine translation models
Neural Machine Translation Framework: PyTorch Repository contaning my implementa
Dark Finix: All in one hacking framework with almost 100 tools
Dark Finix - Hacking Framework. Dark Finix is a all in one hacking framework wit
SatelliteNeRF - PyTorch-based Neural Radiance Fields adapted to satellite domain
SatelliteNeRF PyTorch-based Neural Radiance Fields adapted to satellite domain.
Hl classification bc - A Network-Based High-Level Data Classification Algorithm Using Betweenness Centrality
A Network-Based High-Level Data Classification Algorithm Using Betweenness Centr
Digan - Official PyTorch implementation of Generating Videos with Dynamics-aware Implicit Generative Adversarial Networks
DIGAN (ICLR 2022) Official PyTorch implementation of "Generating Videos with Dyn
S2s2net - Sentinel-2 Super-Resolution Segmentation Network
S2S2Net Sentinel-2 Super-Resolution Segmentation Network Getting started Install
SimCTG - A Contrastive Framework for Neural Text Generation
A Contrastive Framework for Neural Text Generation Authors: Yixuan Su, Tian Lan,
HashNeRF-pytorch - Pure PyTorch Implementation of NVIDIA paper on Instant Training of Neural Graphics primitives
HashNeRF-pytorch Instant-NGP recently introduced a Multi-resolution Hash Encodin
Hierarchical-Bayesian-Defense - Towards Adversarial Robustness of Bayesian Neural Network through Hierarchical Variational Inference (Openreview)
Towards Adversarial Robustness of Bayesian Neural Network through Hierarchical V
Point-NeRF: Point-based Neural Radiance Fields
Point-NeRF: Point-based Neural Radiance Fields Project Sites | Paper | Primary c
GEA - Code for Guided Evolution for Neural Architecture Search
Efficient Guided Evolution for Neural Architecture Search Usage Create a conda e
PINN(s): Physics-Informed Neural Network(s) for von Karman vortex street
PINN(s): Physics-Informed Neural Network(s) for von Karman vortex street This is
A lossless neural compression framework built on top of JAX.
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 module to communicate with Triller's API
A small, UNOFFICIAL module to communicate with Triller's API. I plan to add more features/methods in the future.
Collection of TensorFlow2 implementations of Generative Adversarial Network varieties presented in research papers.
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
B2EA: An Evolutionary Algorithm Assisted by Two Bayesian Optimization Modules for Neural Architecture Search This is the offical implementation of the
You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks.
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
This repository contains code from the paper "TTS-GAN: A Transformer-based Time-Series Generative Adversarial Network"
TTS-GAN: A Transformer-based Time-Series Generative Adversarial Network This repository contains code from the paper "TTS-GAN: A Transformer-based Tim
Tensorflow implementation of our method: "Triangle Graph Interest Network for Click-through Rate Prediction".
TGIN Tensorflow implementation of our method: "Triangle Graph Interest Network for Click-through Rate Prediction". Files in the folder dataset/ electr
PyTorch-Geometric Implementation of MarkovGNN: Graph Neural Networks on Markov Diffusion
MarkovGNN This is the official PyTorch-Geometric implementation of MarkovGNN paper under the title "MarkovGNN: Graph Neural Networks on Markov Diffusi
TorchMD-Net provides state-of-the-art graph neural networks and equivariant transformer neural networks potentials for learning molecular potentials
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
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 Reinforcement Learning for Differing Action Spaces via Q-Network Representations
Transfer-Learning-in-Reinforcement-Learning Transfer Reinforcement Learning for Differing Action Spaces via Q-Network Representations Final Report Tra
Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable.
Diffrax Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. Diffrax is a JAX-based library providing numerical differe
OMLT: Optimization and Machine Learning Toolkit
OMLT is a Python package for representing machine learning models (neural networks and gradient-boosted trees) within the Pyomo optimization environment.
Implemenets the Contourlet-CNN as described in C-CNN: Contourlet Convolutional Neural Networks, using PyTorch
C-CNN: Contourlet Convolutional Neural Networks This repo implemenets the Contourlet-CNN as described in C-CNN: Contourlet Convolutional Neural Networ
MoCap-Solver: A Neural Solver for Optical Motion Capture Data
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 Drug Binding Structure Prediction
EquiBind: geometric deep learning for fast predictions of the 3D structure in which a small molecule binds to a protein
Tensorflow 2 implementation of our high quality frame interpolation neural network
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
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
From Canonical Correlation Analysis to Self-supervised Graph Neural Networks
Code for CCA-SSG model proposed in the NeurIPS 2021 paper From Canonical Correlation Analysis to Self-supervised Graph Neural Networks.
HGCN: Harmonic Gated Compensation Network For Speech Enhancement
HGCN The official repo of "HGCN: Harmonic Gated Compensation Network For Speech Enhancement", which was accepted at ICASSP2022. How to use step1: Calc
DrNAS: Dirichlet Neural Architecture Search
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
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
CATE: Computation-aware Neural Architecture Encoding with Transformers Code for paper: CATE: Computation-aware Neural Architecture Encoding with Trans
A curated list of automated deep learning (including neural architecture search and hyper-parameter optimization) resources.
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
Convolutional Neural Network to detect deforestation in the Amazon Rainforest This project is part of my final work as an Aerospace Engineering studen
PyTorch implementations of the NeRF model described in "NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis"
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.
Price Prediction model is used to develop an LSTM model to predict the future market price of Bitcoin and Ethereum.
Community and sentiment analysis based on tweets
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
UMPNet: Universal Manipulation Policy Network for Articulated Objects Zhenjia Xu, Zhanpeng He, Shuran Song Columbia University Robotics and Automation
Self-Correcting Quantum Many-Body Control using Reinforcement Learning with Tensor Networks
Self-Correcting Quantum Many-Body Control using Reinforcement Learning with Tensor Networks This repository contains the code and data for the corresp
These are Simple python scripts to test/scan your network
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 is an open-source solution for stress testing network devices using different testing methods
PacketPy About PacketPy is an open-source solution for stress testing network devices using different testing methods. Currently, there are only two c
Artificial Neural network regression model to predict the energy output in a combined cycle power plant.
Energy_Output_Predictor Artificial Neural network regression model to predict the energy output in a combined cycle power plant. Abstract Energy outpu
Neural Radiance Fields Using PyTorch
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
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).
Effect of Different Encodings and Distance Functions on Quantum Instance-based Classifiers
Effect of Different Encodings and Distance Functions on Quantum Instance-based Classifiers The repository contains the code to reproduce the experimen
PyZebrascope - an open-source Python platform for brain-wide neural activity imaging in behaving zebrafish
PyZebrascope - an open-source Python platform for brain-wide neural activity imaging in behaving zebrafish
A minimalist tool to display a network graph.
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)
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
SBINN: Systems-biology informed neural network The source code for the paper M. Daneker, Z. Zhang, G. E. Karniadakis, & L. Lu. Systems biology: Identi
Non-Vacuous Generalisation Bounds for Shallow Neural Networks
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: Tone-Octave Network for Singing Melody Extraction from Polyphonic Music
TONet Introduction The official implementation of "TONet: Tone-Octave Network for Singing Melody Extraction from Polyphonic Music", in ICASSP 2022 We
Deep Learning agent of Starcraft2, similar to AlphaStar of DeepMind except size of network.
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
The mini-AlphaStar (mini-AS, or mAS) - mini-scale version (non-official) of the AlphaStar (AS)
A mini-scale reproduction code of the AlphaStar program. Note: the original AlphaStar is the AI proposed by DeepMind to play StarCraft II.
FewBit — a library for memory efficient training of large neural networks
FewBit FewBit — a library for memory efficient training of large neural networks. Its efficiency originates from storage optimizations applied to back
This repository is the code of the paper Accelerating Deep Reinforcement Learning for Digital Twin Network Optimization with Evolutionary Strategies
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
DNA sequence classification by Deep Neural Network: Project Overview worked on the DNA sequence classification problem where the input is the DNA sequ
Pytorch Implementation of "Desigining Network Design Spaces", Radosavovic et al. CVPR 2020.
RegNet Pytorch Implementation of "Desigining Network Design Spaces", Radosavovic et al. CVPR 2020. Paper | Official Implementation RegNet offer a very
A convolutional recurrent neural network for classifying A/B phases in EEG signals recorded for sleep analysis.
CAP-Classification-CRNN A deep learning model based on Inception modules paired with gated recurrent units (GRU) for the classification of CAP phases
Filtering variational quantum algorithms for combinatorial optimization
Current gate-based quantum computers have the potential to provide a computational advantage if algorithms use quantum hardware efficiently.
Code for Phase diagram of Stochastic Gradient Descent in high-dimensional two-layer neural networks
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
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
N-HiTS: Neural Hierarchical Interpolation for Time Series Forecasting Recent progress in neural forecasting instigated significant improvements in the
DiffStride: Learning strides in convolutional neural networks
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.
Build upon neural radiance fields to create a scene-specific implicit 3D semantic representation, Semantic-NeRF
Semantic-NeRF: Semantic Neural Radiance Fields Project Page | Video | Paper | Data In-Place Scene Labelling and Understanding with Implicit Scene Repr
Temporal Dynamic Convolutional Neural Network for Text-Independent Speaker Verification and Phonemetic Analysis
TDY-CNN for Text-Independent Speaker Verification Official implementation of Temporal Dynamic Convolutional Neural Network for Text-Independent Speake
Unofficial Tensorflow 2 implementation of the paper Implicit Neural Representations with Periodic Activation Functions
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.
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
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
Anonymously Reverse shell over Tor Network using Hidden Services without portfortwarding Tor ağı ile Dark Web servislerini kullanarak anonim biçimde p
This repository has automation content to test Arista devices.
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
Recovering-Brain-Structure-Network-Using-Functional-Connectivity Framework: Papers: This repository provides a PyTorch implementation of the models ad
Brain tumor detection using Convolution-Neural Network (CNN)
Detect and Classify Brain Tumor using CNN. A system performing detection and classification by using Deep Learning Algorithms using Convolution-Neural Network (CNN).
A pure PyTorch implementation of the loss described in "Online Segment to Segment Neural Transduction"
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
Sequence-tagging using deep learning
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.
Python project that aims to discover CDP neighbors and map their Layer-2 topology within a shareable medium like Visio or Draw.io.
CRF-RNN for Semantic Image Segmentation - PyTorch version
This repository contains the official PyTorch implementation of the "CRF-RNN" semantic image segmentation method, published in the ICCV 2015
A web porting for NVlabs' StyleGAN2, to facilitate exploring all kinds characteristic of StyleGAN networks
This project is a web porting for NVlabs' StyleGAN2, to facilitate exploring all kinds characteristic of StyleGAN networks. Thanks for NVlabs' excelle
Generate Cartoon Images using Generative Adversarial Network
AvatarGAN ✨ Generate Cartoon Images using DC-GAN Deep Convolutional GAN is a generative adversarial network architecture. It uses a couple of guidelin
Generating retro pixel game characters with Generative Adversarial Networks. Dataset "TinyHero" included.
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.
The unified machine learning framework, enabling framework-agnostic functions, layers and libraries. Contents Overview In a Nutshell Where Next? Overv
Example of semantic segmentation in Keras
keras-semantic-segmentation-example Example of semantic segmentation in Keras Single class example: Generated data: random ellipse with random color o
RuCLIP tiny (Russian Contrastive Language–Image Pretraining) is a neural network trained to work with different pairs (images, texts).
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 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.
Python Assignments for the Deep Learning lectures by Andrew NG on coursera with complete submission for grading capability.
Convolutional neural network that analyzes self-generated images in a variety of languages to find etymological similarities
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 local IP's in your network
IPScanner 🔬 A simple threaded IP-Scanner written in python3 that can monitor lo
An Empirical Review of Optimization Techniques for Quantum Variational Circuits
QVC Optimizer Review Code for the paper "An Empirical Review of Optimization Techniques for Quantum Variational Circuits". Each of the python files ca