Name: Yi Ding
Type: User
Company: Nanyang Technological University
Bio: Ph.D. in Computer Science and Engineering. Research interests: deep/machine learning, brain-computer interface, affective computing, and artificial intelligence
Location: Singapore
Yi Ding's Projects
A collection of AWESOME things about domian adaptation
Let us control diffusion models!
A Convolutional Transformer to decode mental states from Electroencephalography (EEG) for Brain-Computer Interfaces (BCI)
This is the pytorch implementation of EmT, a graph-transformer for EEG emotion recognition.
[EMBC-23] This is the PyTorch implementation of GIGN
[TNNLS-2023] This is the PyTorch implementation of LGGNet.
[IEEE J-BHI-2024] The PyTorch implementation of MASA-TCN
Python script to stream EEG data from the muse 2016 headset
Pytorch implementation of the Graph Attention Network model by Veličković et. al (2017, https://arxiv.org/abs/1710.10903)
My implementation of the original GAT paper (Veličković et al.). I've additionally included the playground.py file for visualizing the Cora dataset, GAT embeddings, an attention mechanism, and entropy histograms. I've supported both Cora (transductive) and PPI (inductive) examples!
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows".
Implementation of Swin Transformer with Pytorch
Thesis Latex Template for Nanyang Technological University (NTU)
Transfer Learning Library for Domain Adaptation and Finetune.
[TAFFC-2022] PyTorch implementation of TSception v2
Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
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