Pinned Repositories
ScalableML
Teaching materials for module COM6012 Scalable Machine Learning, University of Sheffield, 2024
fMRI-site-adaptation
Improving autism identification with multisite data via site-dependence minimisation and second-order functional connectivity (TMI, 2022)
pykale
Knowledge-Aware machine LEarning (KALE): accessible machine learning from multiple sources for interdisciplinary research, part of the 🔥PyTorch ecosystem. ⭐ Star to support our work!
DawfMRI
Improving Whole-Brain Neural Decoding of fMRI with Domain Adaptation
GSDA-Lateralization
Group-specific discriminant analysis for sex differences in lateralization of brain functional network
openfmri
code related to the OpenFMRI project
pydale
Domain Adaptation Learning in Python
pykale
Knowledge-Aware machine LEarning (KALE) for graphs, images, and videos
shef_cni_solution
Code for MICCAI Connectomics in NeuroImaging Challenge 2019
sider
AAAI2020 Side Information Dependence as a Regularizer for Analyzing Human Brain Conditions across Cognitive Experiments
shuo-zhou's Repositories
shuo-zhou/pydale
Domain Adaptation Learning in Python
shuo-zhou/GSDA-Lateralization
Group-specific discriminant analysis for sex differences in lateralization of brain functional network
shuo-zhou/sider
AAAI2020 Side Information Dependence as a Regularizer for Analyzing Human Brain Conditions across Cognitive Experiments
shuo-zhou/pykale
Knowledge-Aware machine LEarning (KALE) for graphs, images, and videos
shuo-zhou/shef_cni_solution
Code for MICCAI Connectomics in NeuroImaging Challenge 2019
shuo-zhou/shuo-zhou.github.io
A beautiful, simple, clean, and responsive Jekyll theme for academics
shuo-zhou/COM6012-ScalableML
COM6012 Scalable Machine Learning - University of Sheffield
shuo-zhou/Dassl.pytorch
A PyTorch toolbox for domain adaptation and semi-supervised learning.
shuo-zhou/fsic-test
ICML 2017. Kernel-based adaptive linear-time independence test.
shuo-zhou/HCPpipelines
Processing pipelines for the HCP
shuo-zhou/ICA-RAMICA
This repository contains the codes used for the following work: Liyan Song, Shuo Zhou, and Haiping Lu "Direct ICA on Data Tensor via Random Matrix Modeling"
shuo-zhou/l1_two_sample_test
shuo-zhou/learning-from-brains
Self-supervised learning techniques for neuroimaging data inspired by prominent learning frameworks in natural language processing + One of the broadest neuroimaging datasets used for pre-training to date.
shuo-zhou/masf
Domain Generalization via Model-Agnostic Learning of Semantic Features
shuo-zhou/medical-data
shuo-zhou/MLAI
Machine Learning And Adaptive Intelligence Module
shuo-zhou/NL-talks
Talks from Neil Lawrence
shuo-zhou/PAWP
shuo-zhou/pl-cni_challenge
Wrapper app to containerise via Docker a solution to CNI 2019 Challenge
shuo-zhou/pytorch-ada
Another Domain Adaptation library, aimed at researchers.
shuo-zhou/readme-with-video
shuo-zhou/remark
A simple, in-browser, markdown-driven slideshow tool.
shuo-zhou/sz144.github.io_
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
shuo-zhou/tensorly
TensorLy: Tensor Learning in Python.
shuo-zhou/the-turing-way
Host repository for The Turing Way: a how to guide for reproducible data science
shuo-zhou/tig-hugo-group
shuo-zhou/transfer
Code and data for the paper "Multi-Source Domain Adaptation with Mixture of Experts" https://arxiv.org/abs/1809.02256
shuo-zhou/transparentML
An Introduction to Transparent Machine Learning
shuo-zhou/turing-meta-learning.github.io
shuo-zhou/WebSlides
Create HTML presentations in seconds —