Guandao Yang

PointFlow. PointFlow : 3D Point Cloud Generation with Continuous Normalizing Flows

NFGP. Pytorch implementation of NeurIPS 2021 paper: Geometry Processing with Neural Fields.

3d-recon. Implementation for paper "Learning Single-View 3D Reconstruction with Limited Pose Supervision".

SWALP. Code for paper "SWALP: Stochastic Weight Averaging forLow-Precision Training".

PNF. Polynomial Neural Fields for Subband Decomposition and Manipulation

WAGE.pytorch. Reproduction of WAGE in PyTorch.

jax-diffusion. Jax implementation of ImageNet diffusion models.

SuperPointEA. Codes for paper "Learning Data-Adaptive Interest Points through Epipolar Adaptation" will be available soon.

NN.jl. Jupiter neural network library

DVGO. Python

awesome-deep-vision. A curated list of deep learning resources for computer vision

self-critical.pytorch. Unofficial pytorch implementation for Self-critical Sequence Training for Image Captioning

awesome-o1. TeX

loss-landscape. Code for visualizing the loss landscape of neural nets

Trace. Trace(AB) = Trace(BA) for all A, B matrices of some commutative rings.

ttt-lm-jax. Official JAX implementation of Learning to (Learn at Test Time): RNNs with Expressive Hidden States

KKDJT. MATLAB

GraphCNN-GAN. Graph-convolutional GAN for point cloud generation. Code from ICLR 2019 paper Learning Localized Generative Models for 3D Point Clouds via Graph Convolution

cvpr18-caption-eval-1. Jupyter Notebook

cornell-cs5785-2022-applied-ml. Lecture materials for Cornell CS5785 Applied Machine Learning (Fall 2022)

ganhacks. starter from "How to Train a GAN?" at NIPS2016

scripts-ubuntu-debian. Scripts for Ubuntu/Debian

dust3r. DUSt3R: Geometric 3D Vision Made Easy

jax-diffusion-transformer. Implementation of Diffusion Transformer (DiT) in JAX