patricia_xiao

@PatriciaXiao · User

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逗比脑洞青年的狂野实验田。 I am not coding, I am bugging.

University of California, Los AngelesLos Angeles, California66 followers176 repositories

Repositories

PatriciaXiao/TIMME

TIMME: Twitter Ideology-detection via Multi-task Multi-relational Embedding (code & data)

★ 75PythonForks 22

PatriciaXiao/headscale-china-kit

Agent skill: deploy a self-hosted Headscale + built-in DERP mesh that stays usable across China's Great Firewall — connect devices in China back to a home base abroad, with a security model that holds even if the VPS is compromised.

★ 0Forks 0

PatriciaXiao/dinov2

PyTorch code and models for the DINOv2 self-supervised learning method.

★ 0Jupyter NotebookForks 0

PatriciaXiao/Viewers

OHIF zero-footprint DICOM viewer and oncology specific Lesion Tracker, plus shared extension packages

★ 0TypeScriptForks 0

PatriciaXiao/PanDerm

[Nature Medicine'25] PanDerm: A Multimodal Vision Foundation Model for Clinical Dermatology

★ 0Forks 0

PatriciaXiao/echo_CLIP

EchoCLIP hhttps://www.nature.com/articles/s41591-024-02959-y official code

★ 0PythonForks 0

PatriciaXiao/mmFormer

[MICCAI 2022] The official code for "mmFormer: Multimodal Medical Transformer for Incomplete Multimodal Learning of Brain Tumor Segmentation"

★ 0Forks 0

PatriciaXiao/TransUNet

This repository includes the official project of TransUNet, presented in our paper: TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation.

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PatriciaXiao/EchoDynamic

EchoNet-Dynamic is a deep learning model for assessing cardiac function in echocardiogram videos.

★ 0Forks 0

PatriciaXiao/mimic3-benchmarks

Python suite to construct benchmark machine learning datasets from the MIMIC-III 💊 clinical database.

★ 0PythonForks 0

PatriciaXiao/Multimodal_Transformer

A Multimodal Transformer: Fusing Clinical Notes With Structured EHR Data for Interpretable In-Hospital Mortality Prediction

★ 0PythonForks 0

PatriciaXiao/plip

Pathology Language and Image Pre-Training (PLIP) is the first vision and language foundation model for Pathology AI. PLIP is a large-scale pre-trained model that can be used to extract visual and language features from pathology images and text description. The model is a fine-tuned version of the original CLIP model.

★ 0Forks 0

PatriciaXiao/SINN

Source code of our KDD 2022 paper: Predicting Opinion Dynamics via Sociologically-Informed Neural Networks

★ 0PythonForks 0

PatriciaXiao/GraphCL

[NeurIPS 2020] "Graph Contrastive Learning with Augmentations" by Yuning You, Tianlong Chen, Yongduo Sui, Ting Chen, Zhangyang Wang, Yang Shen

★ 0PythonForks 0