Sparse Principal Component Analysis (SPCA) using Variable Projection
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Updated
Apr 7, 2018 - R
Sparse Principal Component Analysis (SPCA) using Variable Projection
Comparative analysis of different feature extraction techniques for hyperspectral image classification.
Suit of R-scripts to perform landscape genomic analyses
Sense–Plan–Code–Act (SPCA) framework — LLM+PDDL planning, code generation and ROS2/UR5 simulation for embodied robotic manipulation.
Scripts in R for analyses of Identification of SNPs candidates and GEA and GPA studies - PART 4 in LANDSCAPE GENOMICS PIPELINE
Software for identifying co-evolutionary sectors in proteins using RoCA
Official code repo for STAI-X 2026 paper "Transformer as Provable Approximators of Sparse Principal Component Analysis".
This repo contains the codes, images, report and slides for the project of the course - `MTH514A: Multivariate Analysis` at IIT Kanpur during the academic year 2022-2023.
Sparse Principal Component Analysis on Gene expression data.
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