📄 Configuration files that enhance Cursor AI editor experience with custom rules and behaviors

VoCoT: Unleashing Visually Grounded Multi-Step Reasoning in Large Multi-Modal Models

📌 A JSON to Markdown converter.

Iterative JSON parser with Pythonic interfaces

open-source code for article "Brain-Machine Interactive Neuromodulation Tool with Edge AI Computing"

MATLAB eye tracking test and fixation analysis scripts.

Regression Graph Neural Network (regGNN) for cognitive score prediction.

GCN-GAN: A Non-linear Temporal Link Prediction Model for Weighted Dynamic Networks

Statistical Analysis of Network Data with R, 2nd Edition

Multi-task learning using uncertainty to weigh losses for scene geometry and semantics, Auxiliary Tasks in Multi-task Learning

try to implement the CVPR 2019 paper "Selective Kernel Networks" by PyTorch

Transformer: PyTorch Implementation of "Attention Is All You Need"

🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.

This is an official implementation for "Contextual Transformer Networks for Visual Recognition".

EEG Transformer 2.0. i. Convolutional Transformer for EEG Decoding. ii. Novel visualization - Class Activation Topography.

i. A practical application of Transformer (ViT) on 2-D physiological signal (EEG) classification tasks. Also could be tried with EMG, EOG, ECG, etc. ii. Including the attention of spatial dimension…

source code of “Visual Saliency Transformer” (ICCV2021)

Explainability for Vision Transformers

ResNeSt: Split-Attention Networks

Vision Transformer (ViT) in PyTorch

Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch

The graph attention operator that supports edge attributes

Repetition code of the model for the paper "EEG Emotion Recognition Using Dynamical Graph Convolutional Neural Networks" in pytorch

Implement Long Short-Term Memory(LSTM) with pytorch to handle raw EEG data

Pytorch implementation of Center Loss

Resources for the paper titled "EEG-GCNN: Augmenting Electroencephalogram-based Neurological Disease Diagnosis using a Domain-guided Graph Convolutional Neural Network". Accepted for publication (w…

Graph Neural Network Library for PyTorch