Repository Index

TranslatedLangGPT: Empowering everyone to become a prompt expert! 🚀 📌 Proposer of Structured Prompt 📌 Initiator of Meta-Prompt 📌 The most popular paradigm for putting prompts into practice | Language of GPT The pioneering framework for structured & meta-prompt design 10,000+ ⭐ | Battle-tested by thousands of users worldwide Created by 云中江树 (Yunzhong Jiangshu, "river and trees amid the clouds")

• prompt-engineering
• chatgpt
• deeplearning
• framework

TranslatedBuild your neural network easy and fast, 莫烦Python (Morvan Python) Chinese teaching

• neural-network
• python
• pytorch-tutorial
• batch-normalization

This repo contains the source code in my personal column (https://zhuanlan.zhihu.com/zhaoyeyu), implemented using Python 3.6. Including Natural Language Processing and Computer Vision projects, such as text generation, machine translation, deep convolution GAN and other actual combat code.

• deep-learning
• tensorflow-examples
• convolutional-neural-networks
• recurrent-neural-networks

[CVPR 2021] Official PyTorch implementation for Transformer Interpretability Beyond Attention Visualization, a novel method to visualize classifications by Transformer based networks.

• deep-learning
• vision-transformer
• bert-model
• bert

An experimentation and research platform to investigate the interaction of automated agents in an abstract simulated network environments.

A scikit-learn-compatible Python implementation of ReBATE, a suite of Relief-based feature selection algorithms for Machine Learning.

• feature-selection
• data-science
• python

Reference mapping for single-cell genomics

• single-cell
• deep-learning
• rna-seq-analysis
• data-integration

scPerturb: A resource and a python/R tool for single-cell perturbation data

• cite-seq
• database
• perturbation
• scatac-seq

🏃 The go-to single-cell Foundation Model

• batch-correction
• cell-biology
• celltype-annotation
• denoising

Code for "Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution", NeurIPS 2022.

• disentanglement
• drug-discovery
• genomics
• perturbation

PRnet is a flexible and scalable perturbation-conditioned generative model predicting transcriptional responses to unseen complex perturbations at bulk and single-cell levels.

High-Dimensional Gene Expression and Morphology Profiles of Cells across 28,000 Genetic and Chemical Perturbations