yrjzsbg

yrjzsbg's Stars

• matlab-deep-learning/transformer-networks-for-time-series-prediction

  Deep Learning in Quantitative Finance: Transformer Networks for Time Series Prediction

  Language:MATLAB395

• fortuneSuyue/CNN-BiGRU-AM

  This repository includes code for the paper: Lithology Identification Based on One-dimensional Convolutional Neural Network and Recurrent Neural Network with Attention Mechanism.

  Language:Jupyter Notebook121

• Sameh20200218AI/NLP_Emotions_Text_Classification_Using_Recurrent_and_Attention_Mechanism

  Using CNN & RNN & GRU & LSTM & BiRNN & BiGRU & BiLSTM & Transformers for Emotions Sentimental Analysis

  Language:Jupyter Notebook3

• HelloCC1422/CNN-BiGRU-Attention

  CNN-BiGRU-Attention模型

  Language:Python836

• CESTlabZu/DCAE-CEST

  DCAE-CEST: : The DCAE-CEST method can learn the most important features of the CEST Z-spectrum and provide the most effective denoising solution with high fidelity of the data

  21

• nyirobalazs/epilepsy-prediction-with-machine-learning

  Epilepsy Prediction with CNN-BiLSTM | BSc dissertation project

  Language:MATLAB152

• eteohx/EEG_cocktail_decoding

  Decode auditory attention from EEG within the context of a two-speaker cocktail party paradigm

  Language:MATLAB3

• carolinemyers/PSA-pupil

  Two scripts designed to (1) pre-process raw pupil time-series data and (2) visualize baseline-normalized individual trial-level and average pupil size data across 3 uncertainty conditions in a pre-saccadic visual attention task

  Language:MATLAB1

• Codelover-aashi/Signal-processing---EEG

  Attention recognition using EEG signals - The EEG signals are pre-processed and further used for recognizing attention.

  Language:MATLAB1

• artipago/Travelling-waves-EEG-2.0

  This code analyzes traveling waves in EEG signals. It can be apply to any dataset, but it is based on the data available here: https://osf.io/pn784/. For details, please refer to this paper: "Distinct roles of forward and backward alpha-band waves in spatial visual attention" - https://www.biorxiv.org/content/10.1101/2022.08.18.504422v1.abstract

  Language:MATLAB72

• syedajannatulferdous121/transformer

  The MATLAB code implements a Transformer model, a recent innovation in deep neural networks. It includes modules for multi-head attention and feed-forward layers, enabling advanced sequence modeling and feature extraction. The code can be used for various tasks such as natural language processing and time series analysis.

  Language:MATLAB61

• samoliverschumacher/neuralnets

  A home-brewed MATLAB Library for NNets - LSTMs with Attention

  Language:MATLAB71

• Yorkson-huang/CNN-LSTM-Attention-Prediction

  Language:MATLAB14

• msdamzdh/AttentionLayer

  This MATLAB script defines a custom attention layer class `attentionLayer` that can be used in deep learning models, particularly for sequence-to-sequence tasks or transformer-based architectures.

  Language:MATLAB2

• thomasxiaodongwu/SomeCNNBymatLab

  BILSTM，GRU，LSTM

  Language:MATLAB131

• tschmoog/Radial-Basis-Functions

  Two radial basis functions that were used to find an underlying signal in noisy 10 dimentional data. The initial RBF is fairly standard, with the second RBF having the ability to grow and prune neurons as required as real time data is presented to it.

  Language:Matlab2

• arnavks97/Supervised-Machine-Learning

  Approximation and Classification example problems solved utilizing MLP (Multi Layer Perceptron) and RBF (Radial Basis Function) Neural Networks.

  Language:Matlab31

• santosst3/ANN4Octave

  Codes for creating and training MLP and RBF ANNs

  Language:MATLAB1

• phioeffn/Energy_stable_RBF

  Code for the paper "Energy-stable global radial basis function methods on summation-by-parts form"

  Language:MATLAB2

• romavini/RBF-forecast

  A time-series forecasting algorithm based in Radial Basis Function Neural Networks, in Matlab.

  Language:MATLAB3

• keya-desai/Neural-Networks

  Implementation of MLP and RBF

  Language:Matlab2

• jpac1207/RBF_Neural_Network_Matlab

  Implementation from a RBF NN

  Language:MATLAB2

• stella7/Classifier

  Classify a dataset using five different classifiers including k-NN, Support Vector Machine (with RBF kernel), Naïve Bayes, Decision Trees and Neural Networks. The objective is to experiment with parameter selection in training classifiers and to compare the performance of these well- known classification methods.

  Language:Matlab54

• Omid-SH/EEG_signal_classification

  EEG signal classification using Neural Networks, RBF, and genetic algorithm

  Language:MATLAB4

• noob-rex/RBFNN

  A properly designed radial basis function neural network (RBFNN) trained with features can recognize, classify and locate faults faster as it utilizes only half cycle data after fault initiation.

  Language:MATLAB3

• FatemehGholamzadeh/train-RBF-NN

  training a RBF network Using ES algorithm - Computational Intelligence Course (Spring 2019)

  Language:MATLAB5

• JensSettelmeier/EE7207-Neural-and-Fuzzy-Systems-NTU

  RBF Neural Network with Self Organazing Map to solve classification problem.

  Language:MATLAB9

• RasitEvduzen/RBFNeuralNetwork

  Language:MATLAB1

• stxupengyu/PSO-RBF-NN

  使用粒子群算法优化的RBF神经网络进行预测。RBF neural network optimized by particle swarm optimization is used for prediction.

  Language:MATLAB9317

• stxupengyu/BP-RBF-Prediction

  使用BP神经网络、RBF神经网络以及PSO优化的RBF神经网络进行数据的预测

  Language:MATLAB18540