Python Parametric Resources

HeadNeRF: A Real-time NeRF-based Parametric Head Model This repository contains a pytorch implementation of "HeadNeRF: A Real-time NeRF-based Parametr

Unsupervised Audio Source Separation Using Differentiable Parametric Source Models This is the source code for the experiments related to the paper Un

jumpdiff jumpdiff is a python library with non-parametric Nadaraya─Watson estimators to extract the parameters of jump-diffusion processes. With jumpd

Introduction English | 简体中文 MMHuman3D is an open source PyTorch-based codebase for the use of 3D human parametric models in computer vision and comput

Package: dsm Python package dsm provides an API to train the Deep Survival Machines and associated models for problems in survival analysis. The under

Fast Symbolic Regression Symbolic Regression is a non-linear, non-parametric Machine Learning method capable of modeling complex data sets. fastsr aim

Parametric-Contrastive-Learning This repository contains the implementation code for ICCV2021 paper: Parametric Contrastive Learning (https://arxiv.or

Parametric Bottle using CADQuery The proposed code makes it possible to generate different types and sizes of 3D bottles in order to train Pixel2mesh

Unofficial implementation: MoCo: Momentum Contrast for Unsupervised Visual Representation Learning (Paper) InsDis: Unsupervised Feature Learning via N

A python parametric CAD scripting framework based on OCCT

openmc-plasma-source This python-based package offers a way of creating a parametric OpenMC plasma source from plasma parameters. The OpenMC sources a

Fully Adversarial Mosaics (FAMOS) Pytorch implementation of the paper "Copy the Old or Paint Anew? An Adversarial Framework for (non-) Parametric Imag

DAG Amendment for Inverse Control of Parametric Shapes This repository is the official Blender implementation of the paper "DAG Amendment for Inverse

The Parametric Voron This repository contains Fusion 360 reconstructions of various printed parts from the Voron printers

Parametric-Contrastive-Learning This repository contains the implementation code for ICCV2021 paper: Parametric Contrastive Learning (https://arxiv.or

NPMs: Neural Parametric Models Project Page | Paper | ArXiv | Video NPMs: Neural Parametric Models for 3D Deformable Shapes Pablo Palafox, Aljaz Bozic

DanceNet3D The personal repository of the work: DanceNet3D: Music Based Dance Generation with Parametric Motion Transformer. Dataset and Results Pleas

Fully Adversarial Mosaics (FAMOS) Pytorch implementation of the paper "Copy the Old or Paint Anew? An Adversarial Framework for (non-) Parametric Imag

A parametric soroban written in CADQuery The purpose of this project is to demonstrate how "code CAD" can be intuitive to learn. See soroban.py for a

We challenge a common assumption underlying most supervised deep learning: that a model makes a prediction depending only on its parameters and the features of a single input. To this end, we introduce a general-purpose deep learning architecture that takes as input the entire dataset instead of processing one datapoint at a time.

Freedom to build what you want FreeCAD is an open-source parametric 3D modeler made primarily to design real-life objects of any size. Parametric modeling allows you to easily modify your design by going back into your model history to change its parameters.