Extending Sparse Dictionary Learning Methods for Adversarial Robustness
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Updated
Nov 12, 2023
Extending Sparse Dictionary Learning Methods for Adversarial Robustness
Supervised and Unsupervised latent space models
The project is about text sunmmarization with sparse coding
A set of scripts and experiments making it easier to analyze deep learning empirically.
sparsely-encoded poisson matrix factorization
Presentation slides relevant to invited and contributed talks
SPARSE + CELP lossy signal compression codecs
Gamma Lasso Sparse Normal and Logistic Factor Analysis
Early stages of incorporating self-supervised with algorithm unrolling. Code was written as part of a master's thesis (60 ECTS) at Aalborg University, Denmark.
Sparse Matrix Library for GPUs, CPUs, and FPGAs via CUDA, OpenCL, and oneAPI
Chinese Historical Phonology
This repo for the paper titled "SC-MIL: Sparsely Coded Multiple Instance Learning for Whole Slide Image Classification"
My undergrad thesis
Course @ NeuroSchool PhD Program in Neuroscience
PyTorch implementation, with CUDA support, of the sparse coding algorithm based on the paper by Olshausen and Field (1997).
HTM and sparse representation of MNIST
Master's thesis about sparse approximation and dictionary learning using Cloud K-SVD for image denoising. Results show that the algorithm is able to learn sparse representations of signal vectors from distributed data samples in a heterogeneous network setup.
Edge co-occurrences can account for rapid categorization of natural versus animal images
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