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Name: Jesus Perez Curbelo
Type: User
Company: University of Saskatchewan
Location: Saskatoon, SK, canada
Name: Jesus Perez Curbelo
Type: User
Company: University of Saskatchewan
Location: Saskatoon, SK, canada
[ICIMCS'2017] Official Code for 3D Human Body Reshaping with Anthropometric Modeling
Bertini 2.0: The redevelopment of Bertini in C++.
Scripts to explore the CAMELS_spat dataset and process them into the proper format to be used as input for the NH lstm models.
Accompanying code for our HESS paper "Towards learning universal, regional, and local hydrological behaviors via machine learning applied to large-sample datasets"
Collection of advice and resources for getting a job as data scientist
Groebner bases in pure Julia
Code accompanying my blog post: So, what is a physics-informed neural network?
Anthropometric measurement extraction using single image
Official Code for "A methodology for realistic human shape reconstruction from 2D images"
Code repo for publication at https://hess.copernicus.org/articles/26/5085/2022/
https://github.com/kotlin-hands-on/jvm-js-fullstack
Experiments with Mass Conserving LSTMs
Python Script to Convert .mat structured dataset of MPII Human Pose Annotations Dataset into .csv for more convenient understanding
Python library to train neural networks with a strong focus on hydrological applications.
A library for solving differential equations using neural networks based on PyTorch, used by multiple research groups around the world, including at Harvard IACS.
Implementation and testing for the method in https://www.scirp.org/journal/paperinformation.aspx?paperid=67010
This repository contains a number of Jupyter Notebooks illustrating different approaches to solve partial differential equations by means of neural networks using TensorFlow.
PINNs-TF2, Physics-informed Neural Networks (PINNs) implemented in TensorFlow V2.
Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations
PyDEns is a framework for solving Ordinary and Partial Differential Equations (ODEs & PDEs) using neural networks
:spider_web: A Python interface to CGAL's meshing tools
A package for the sparse identification of nonlinear dynamical systems from data
Exploring "A Runge-Kutta Toolkit"
A collection of functionality around rooted trees to generate order conditions for Runge-Kutta methods in Julia for differential equations and scientific machine learning (SciML)
Modern Approaches to Profiling in Python with Scalene
Efficient and Scalable Physics-Informed Deep Learning and Scientific Machine Learning on top of Tensorflow for multi-worker distributed computing
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.