Popular GitHub Repositories for Point Processes

aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

Machine learning, in numpy

A resource repository for 3D machine learning

Research and development (R&D) is crucial for the enhancement of industrial productivity, especially in the AI era, where the core aspects of R&D are mainly focused on data and models. We are committed to automating these high-value generic R&D processes through our open source R&D automation tool RD-Agent, which lets AI drive data-driven AI.

OpenMMLab's next-generation platform for general 3D object detection.

PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation

OpenPCDet Toolbox for LiDAR-based 3D Object Detection.

PointNet and PointNet++ implemented by pytorch (pure python) and on ModelNet, ShapeNet and S3DIS.

StarVector is a foundation model for SVG generation that transforms vectorization into a code generation task. Using a vision-language modeling architecture, StarVector processes both visual and textual inputs to produce high-quality SVG code with remarkable precision.

A highly efficient implementation of Gaussian Processes in PyTorch

A collection of scientific methods, processes, algorithms, and systems to build stories & models.

A collection of scientific methods, processes, algorithms, and systems to build stories & models.

PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space

NMA Computational Neuroscience course

VIP cheatsheets for Stanford's CS 221 Artificial Intelligence

Pytorch framework for doing deep learning on point clouds.

A library for accelerating Transformer models on NVIDIA GPUs, including using 8-bit floating point (FP8) precision on Hopper and Ada GPUs, to provide better performance with lower memory utilization in both training and inference.

Fast and Easy Infinite Neural Networks in Python

Pointcept: a codebase for point cloud perception research. Latest works: PTv3 (CVPR'24 Oral), PPT (CVPR'24), OA-CNNs (CVPR'24), MSC (CVPR'23)