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Dimitris Papatheodorou's Projects

image-manipulator icon image-manipulator

3-part C++ coded academic project that converts images from/to ppm and cpi format, compresses them to rle format using a run length encoding algorithm applied on blocks - data structures the image is split and also applies multiple filters such as gray, color, median, blur, diff

interiorpointalgorithm icon interiorpointalgorithm

A simple Python implementation of the Interior Point algorithm with logarithmic barriers and Newton method with backtracking. It contains an example.

kaggle icon kaggle

A collection of Kaggle solutions. Not very polished.

kaggle-course icon kaggle-course

Kernel for the Kaggle course of Aalto University about Porto Seguro's Safe Driver competition

made-with-ml icon made-with-ml

Learn how to responsibly develop, deploy and maintain production machine learning applications.

metrics icon metrics

Machine learning evaluation metrics, implemented in Python, R, Haskell, and MATLAB / Octave

ml-from-scratch icon ml-from-scratch

Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.

nssm-gp icon nssm-gp

Non-stationary spectral mixture kernels implemented in GPflow

pygcn icon pygcn

Graph Convolutional Networks in PyTorch

pylog icon pylog

A miniProlog interpreter that possibly may support DCG implemented in Python

pythoncompiler icon pythoncompiler

A compiler for the language "Mini Python", created using sablecc.

pytorch-capsule icon pytorch-capsule

Pytorch implementation of Hinton's Dynamic Routing Between Capsules

secondeyes icon secondeyes

A voice command assistant, created for the Human-Computer Interaction course of the CS department @ Athens University of Economics and Business

sylvester-flows icon sylvester-flows

Forked version of Sylvester flows that works with Python 3.7 and PyTorch 1.1

tcrgp icon tcrgp

TCRGP, a novel Gaussian process method that can predict if TCRs recognize certain epitopes. This method can utilize different CDR sequences from both TCRα and TCRβ chains from single-cell data and learn which CDRs are important in recognizing the different epitopes.

textasgraphclassification icon textasgraphclassification

Text transformed to a graph-of-words in order to be classified using graph kernels and a Convolutional Neural Network.

tf2_course icon tf2_course

Notebooks for my "Deep Learning with TensorFlow 2 and Keras" course

variational-autoencoder icon variational-autoencoder

Variational autoencoder implemented in tensorflow and pytorch (including inverse autoregressive flow)

variationalautoencoders icon variationalautoencoders

Comparison of Variational Autoencoders with Bayesian Neural Networks. Accuracy, Latent space, Reconstruction and White Noise filtering.

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