Kartheek Kumar Reddy's Projects
Brain Computer Interface(BCI) data is transformed and banked by BCI from human brain action to.Sparse Bayesian learning is a machine learning method.Its high efficiency of calculation meets the requirement of the analysis of the Brain Computer Interface Data.Here we use Sparse Bayesian linear Discriminant Analysis(SBDA) and its variant as models to classify the electroencephalogram (EEG) tested in P300 dataset from the BCI competition 2004.Through a series of pre-process including bandpass filtering , normalized , time trial extractionļ¼downsampleļ¼winsorizeļ¼etc , their data recognized by SBDA achieves the accuracy achievable with Support Vector Machine(SVM) .Moreover,the computational complexity of SVM is much higher than SBDA and its variant.
Sparse and Regularized Discriminant Analysis in R
This is a Git repository for sparse kernel optimal scoring (sparse KOS).
:exclamation:Ā ThisĀ isĀ aĀ read-onlyĀ mirrorĀ ofĀ theĀ CRANĀ RĀ packageĀ repository. sparseLDAĀ āĀ SparseĀ DiscriminantĀ Analysis.Ā Homepage:Ā http://www.imm.dtu.dk/~lhc,Ā https://github.com/topepo/sparselda
tensor-train tensor completion (T3C), which is based on tt decomposition and gradient descent.
tensor completion/tensor recovery from Gaussian measurements by tensor nuclear norm minimization
Tensor robust PCA (TRPCA) and tensor completion based on tensor nuclear norm under linear transform
Tensor Robust Principal Component Analysis (TRPCA) based on a new tensor nuclear norm
Generating images from text using AttnGAN. (Inference only)
Tensor ring low-rank factors (AAAI 2019)
Deep Unfolding Network for Image Super-Resolution (CVPR, 2020) (PyTorch)
This repo contains the zip file of nintendo emulators and few nintendo games (ROM files). An instruction video is also present.
ImageNet classification using binary Convolutional Neural Networks