Yulu's Projects
Codebase for ARDTs
A collection of open-source dataset to train instruction-following LLMs (ChatGPT,LLaMA,Alpaca)
A curated list of papers in Test-time Adaptation, Test-time Training and Source-free Domain Adaptation
A curated list of prompt-based paper in computer vision and vision-language learning.
Brain-Inspired Modular Training (BIMT), a method for making neural networks more modular and interpretable.
[CVPR22] Official Implementation of DAFormer: Improving Network Architectures and Training Strategies for Domain-Adaptive Semantic Segmentation
High Quality Monocular Depth Estimation via Transfer Learning
Code for "Embodied Intelligence via Learning and Evolution", Gupta et al, Nature Communications
End-to-End Object Detection with Transformers
Code for the Proceedings of the National Academy of Sciences 2020 article, "Understanding the Role of Individual Units in a Deep Neural Network"
Implementation of Forward Forward Network proposed by Hinton in NIPS 2022.
Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.
Generative Agents: Interactive Simulacra of Human Behavior
A beautiful, simple, clean, and responsive Jekyll theme for academics
Codebase for "InstructCV: Instruction-Tuned Text-to-Image Diffusion Models as Vision Generalists"
code for the intelligent car project
Inference code for LLaMA models
Port of Facebook's LLaMA model in C/C++
Code release for "Masked-attention Mask Transformer for Universal Image Segmentation"
code for the 1st prize medical robot in World Cup Robot Competition
OpenMMLab Detection Toolbox and Benchmark
Monocular Depth Estimation Toolbox based on MMSegmentation.
The next-generation platform to monitor and optimize your AI costs in one place 🚀
Open-Sora: Democratizing Efficient Video Production for All
Painter & SegGPT Series: Vision Foundation Models from BAAI
Pix2Seq codebase: multi-tasks with generative modeling (autoregressive and diffusion)
PyTorch implementations of Generative Adversarial Networks.
An implementation of an RBF layer/module using PyTorch.