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2048ai_solver

amodal-instance-seg-asbu

anole

Anole: An Open, Autoregressive and Native Multimodal Models for Interleaved Image-Text Generation

ass1-cs534

autograd_pytorch

Building your own autograd mechanism based on PyTorch tensor only (not Variable, can be seen as numpy array)

caffe

Caffe: a fast open framework for deep learning.

catvton

CatVTON is a simple and efficient virtual try-on diffusion model with 1) Lightweight Network (899.06M parameters totally), 2) Parameter-Efficient Training (49.57M parameters trainable) and 3) Simplified Inference (< 8G VRAM for 1024X768 resolution).

cs231n

Assignments from CS231n written in Python and PyTorch

cs534_machine_learning

deep-learning-tutorials

Series of Deep Learning Tutorials

deep-live-cam

real time face swap and one-click video deepfake with only a single image (uncensored)

drl

This is the repository for hosting for deep reinforcement learning project - CS533

drnet_cvpr2017

Detecting Visual Relationships with Deep Relational Networks

ducminhkhoi.github.io

effective-python

This repository contains the Jupyter Notebook of the Book: "Effective Python" by Brett Slatkin

em_capsules

Pytorch Implementation of EM capsules in the paper "Matrix capsules with EM routing"

falldetection

fapis

feature-weighting-and-boosting

This is the unofficially official implementation of the paper "Feature Weighting and Boosting for Few-Shot Segmentation"

fluent-python-tutorial

This repository contains the Jupyter Notebook of the Book: "Fluent Python" by Luciano ramalho

gpt-2

Code for the paper "Language Models are Unsupervised Multitask Learners"

high-performance-python

Demo of code in the book "High Performance Python" by Micha Gorelick & Ian Ozsvald

ifs-rcnn

iFS-RCNN: An Incremental Few-shot Instance Segmenter (CVPR 2022)

image-captioning

interpretablecnn

lumina-mgpt

mac_network

This is the Pytorch implementation of Compositional Attention Networks for Machine Reasoning

machine-learning-tutorials

machine_learning

Summary of Machine Learning: A Probabilistic Perspective book

mar

PyTorch implementation of MAR+DiffLoss https://arxiv.org/abs/2406.11838