Python Physical-quantities Resources

Paperless-ngx Paperless-ngx is a document management system that transforms your physical documents into a searchable online archive so you can keep,

Sionna: An Open-Source Library for Next-Generation Physical Layer Research Sionna™ is an open-source Python library for link-level simulations of digi

Fixing Malfunctional Objects With Learned Physical Simulation and Functional Prediction Figure 1. Teaser. Introduction This paper studies the problem

Noether Networks: meta-learning useful conserved quantities This repository contains the code necessary to reproduce experiments from "Noether Network

ComPhy This repository holds the code for the paper. ComPhy: Compositional Physical Reasoning ofObjects and Events from Videos, (Under review) PDF Pro

The best way to use this material is by forking it by click the Fork button at the top, right corner. Then you will get your own copy to play with! Th

Pose Detection Project Description: Human pose estimation from video plays a critical role in various applications such as quantifying physical exerci

Monte Carlo Simulation to the Paper A High-Level Fusion Scheme for Circular Quantities published at the 20th International Conference on Advanced Robotics

A Python application that helps users determine their calorie intake, and automatically generates customized weekly meal and workout plans based on metrics computed using their physical parameters

STARCH (Storm Tracking And Regional CHaracterization) STARCH computes regional extreme storm physical and moisture balance characteristics based on sp

DUQ is a python package for working with physical Dimensions, Units, and Quantities.

PhysConsts A Python package that provides physical constants. The code is being developed by Marc van der Sluys of the department of Astrophysics at t

Paperless-ng Paperless (click me) is an application by Daniel Quinn and contributors that indexes your scanned documents and allows you to easily sear

POPPY: Physical Optics Propagation in Python POPPY (Physical Optics Propagation in Python) is a Python package that simulates physical optical propaga

Code Artifacts Code artifacts for the submission "Mind the Gap! A Study on the Transferability of Virtual vs Physical-world Testing of Autonomous Driv

Python package for analyzing sensor-collected human motion data

Physical Anomalous Trajectory or Motion (PHANTOM) Dataset Description This dataset contains the six different classes as described in our paper[]. The

Flexible Networks for Learning Physical Dynamics of Deformable Objects (2021) By Jinhyung Park, Dohae Lee, In-Kwon Lee from Yonsei University (Seoul,

Cryptick is a stock ticker for cryptocurrency tokens, and a physical NFT. This repository includes tools and documentation for the Cryptick device.

p0znMITM ARP Poisoning Tool What is ARP? Address Resolution Protocol (ARP) is a protocol or procedure that connects an ever-changing IP address to a f

Official code of APHYNITY Augmenting Physical Models with Deep Networks for Complex Dynamics Forecasting (ICLR 2021, Oral) Yuan Yin*, Vincent Le Guen*

Principled S2R Dehazing This repository contains the official implementation for PSD Framework introduced in the following paper: PSD: Principled Synt

FCA: Learning a 3D Full-coverage Vehicle Camouflage for Multi-view Physical Adversarial Attack Case study of the FCA. The code can be find in FCA. Cas

RBSRICNN: Raw Burst Super-Resolution through Iterative Convolutional Neural Network An official PyTorch implementation of the RBSRICNN network as desc

Cascade Drone Swarm Physical Demonstration Project Table of Contents About The Project Built With Getting Started Prerequisites Installation About The

Delayed Propagation Transformer: A Universal Computation Engine towards Practical Control in Cyber-Physical Systems Introduction Multi-agent control i

Physion: Evaluating Physical Prediction from Vision in Humans and Machines This repo contains code and data to reproduce the results in our paper, Phy

IsoGCN The official implementation of IsoGCN, presented in the ICLR2021 paper Isometric Transformation Invariant and Equivariant Graph Convolutional N

API to fetch elements of the periodic table in JSON format. Uses Pandas for dumping .csv data to .json and Flask for API Integration. Deployed on "pyt

Phy-Q: A Benchmark for Physical Reasoning Cheng Xue*, Vimukthini Pinto*, Chathura Gamage* Ekaterina Nikonova, Peng Zhang, Jochen Renz School of Comput

Leibniz is a python package which provide facilities to express learnable partial differential equations with PyTorch

An Introduction to Deep Learning for the Physical Layer An usable PyTorch implementation of the noisy autoencoder infrastructure in the paper "An Intr

Deep Learning for Physical Processes: Integrating Prior Scientific Knowledge: Official Pytorch implementation of ICLR 2018 paper Deep Learning for Phy

Physics-Aware Training (PAT) is a method to train real physical systems with backpropagation. It was introduced in Wright, Logan G. & Onodera, Tatsuhiro et al. (2021)1 to train Physical Neural Networks (PNNs) - neural networks whose building blocks are physical systems.