-
Peking University
- Beijing, China
Highlights
- Pro
Stars
Spatial-eXpression-R: Cell type identification (including cell type mixtures) and cell type-specific differential expression for spatial transcriptomics
LIANA+: an all-in-one framework for cell-cell communication
NicheNet: predict active ligand-target links between interacting cells
Multimodal Spatial-Omics Reveal Co-Evolution of Alveolar Progenitors and Proinflammatory Niches in Progression of Lung Precursor Lesions
[CVPR'23] Histopathology Whole Slide Image Analysis with Heterogeneous Graph Representation Learning
Mapping out the coarse-grained connectivity structures of complex manifolds.
The PatchCamelyon (PCam) deep learning classification benchmark.
Diffusion-based all-atom protein generative model.
Machine learning project for Virtual Staining which published in Science Advances!
PyTorch implementation of "Image-to-Image Translation Using Conditional Adversarial Networks".
Scaling up spatial transcriptomics for large-sized tissues: uncovering cellular-level tissue architecture beyond conventional platforms
Official repository for the Boltz biomolecular interaction models
Chai-1, SOTA model for biomolecular structure prediction
A trainable PyTorch reproduction of AlphaFold 3.
An Easy-to-use, Scalable and High-performance RLHF Framework based on Ray (PPO & GRPO & REINFORCE++ & TIS & vLLM & Ray & Dynamic Sampling & Async Agentic RL)
主要记录大语言大模型(LLMs) 算法(应用)工程师相关的知识及面试题