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
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).
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
HTM and sparse representation of MNIST
A curated reading list of research in Sparse Autoencoders and related topics in Mechanistic Interpretability
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.
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