Name: Soyeon BAK
Type: User
Company: @MAILAB-korea
Bio: ~2022.02 Dongguk Univ. Statistics 2022.03~ Korea Univ, AI________
Interested in : Brain-Computer Interface, Meta-learning, Statistics
Location: Seoul, Republic of Korea
Blog: http://mailab.korea.ac.kr/
Soyeon BAK's Projects
This is the Army Research Laboratory (ARL) EEGModels Project: A Collection of Convolutional Neural Network (CNN) models for EEG signal classification, using Keras and Tensorflow
NeurIPS2023 - A generic biosignal learning framework. Large EEG pre-trained models.
😸 Soothing pastel theme for the high-spirited!
Forked repository for developing CD-FSL frameworks / this repository is originated from Cross-Domain Few-Shot Learning Benchmarking System (ECCV 2020) and created by IBM AI Team
The original code for the paper "How to train your MAML" along with a replication of the original "Model Agnostic Meta Learning" (MAML) paper in Pytorch.
A PowerPoint add-in allowing you to insert LaTeX equations into PowerPoint presentations on Windows and Mac
Elegant PyTorch implementation of paper Model-Agnostic Meta-Learning (MAML)
Notebooks and pre-processing code for a meta learning paper/project involving the classification of EEG spectrograms.
Simple project starter kit for 2022-2R APPLICATIONS AND PRACTICE IN NEURAL NETWORKS
Universal Representation Learning from Multiple Domains for Few-shot Classification - ICCV 2021, Cross-domain Few-shot Learning with Task-specific Adapters - CVPR 2022
Reduced version of CDFSL for XAI611 project II ( most python files are originated from https://github.com/IBM/cdfsl-benchmark )