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activelearningsynthetic

autograd

Efficiently computes derivatives of numpy code.

bayesianoptimization

A Python implementation of global optimization with gaussian processes.

cs571

cs571hw

csci571_web_technology

USC_CSCI571_web_technologies_homework_18spring

dc-ign

The Deep Convolutional Inverse Graphics Network

diffusion_model

disentanglement_lib

disentanglement_lib is an open-source library for research on learning disentangled representations.

disentangling-vae

Experiments for understanding disentanglement in VAE latent representations

docs

TensorFlow documentation

expert_readed_books

2021年最新总结，推荐工程师合适读本，计算机科学，软件技术，创业，**类，数学类，人物传记书籍

fucking-algorithm-book

《labuladong的算法小抄》顺序阅读版

fun-with-mnist

Playing with MNIST. Machine Learning. Generative Models.

gan-tutorial

Simple Implementation of many GAN models with PyTorch.

geos

Geometry Engine, Open Source

implementation_variational-auto-encoder

Simple implementation of Variational Autoencoder

improved_wgan_training

Code for reproducing experiments in "Improved Training of Wasserstein GANs"

infogan-pytorch

PyTorch Implementation of InfoGAN

infogan-pytorch-1

implement infoGAN using pytorch

joint-vae

Pytorch implementation of JointVAE, a framework for disentangling continuous and discrete factors of variation :star2:

junjie.github.io

leetcode_record

Record tips/comments/highlights during practicing on leetcode

machine-learning-interviews

This repo is meant to serve as a guide for Machine Learning/AI technical interviews.

new-grad-2024

👋 Hey there new grad🎉! We've put together a collection of full-time job openings for SWE, Quant, PM and tech roles in 2024! 🚀

repaint

Official PyTorch Code and Models of "RePaint: Inpainting using Denoising Diffusion Probabilistic Models", CVPR 2022

score_sde

Official code for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)

tensorflow_dcign

Deep Convolutional Inverse Graphics network (DCIGN) implementation with Tensorflow

uscthesis

a LaTeX style for theses and dissertations at USC