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Name: Nikolaos Dionelis

Type: User

Company: Imperial College London, London, U.K.

Bio: Nikolaos is a postgraduate researcher in the Speech and Audio Processing Group in the Department of Electrical Engineering at Imperial College London (ICL).

Location: London, U.K.

Blog: https://www.commsp.ee.ic.ac.uk/~sap/people-nikolaos-dionelis/

Nikolaos Dionelis's Projects

lucid

A collection of infrastructure and tools for research in neural network interpretability.

lws

Fast spectrogram phase recovery using Local Weighted Sums (C/Python/Matlab)

machine-learning-for-software-engineers

A complete daily plan for studying to become a machine learning engineer.

machine-learning-kd-diagnosis

Diagnosing Kawasaki Disease using Deep Learning and Machine Learning

machine-learning-links-and-lessons-learned

List of all the lessons learned, best practices, and links from my time studying machine learning

maracas

maracas is a library for corrupting audio files with additive and convolutive noise.

maskrcnn-benchmark

Fast, modular reference implementation of Semantic Segmentation and Object Detection algorithms in PyTorch.

matlab-toolbox-for-dnn-based-speech-separation

This folder contains Matlab programs for a toolbox for supervised speech separation using deep neural networks (DNNs).

matrix-routines

Implementations of matrix factorization/completion (and something related) algorithms

medal

Matlab Environment for Deep Architecture Learning

mit-deep-learning-book-pdf

MIT Deep Learning Book in PDF format (complete and parts) by Ian Goodfellow, Yoshua Bengio and Aaron Courville

mixture-density-networks-for-distribution-and-uncertainty-estimation

A generic Mixture Density Networks (MDN) implementation for distribution and uncertainty estimation by using Keras (TensorFlow)

ml-from-scratch

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

ml-videos

A collection of video resources for machine learning

mlalgorithms

Minimal and clean examples of machine learning algorithms implementations

MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.

mml-book.github.io

Companion webpage to the book "Mathematics For Machine Learning"

modeling-nonlinear

Audio examples for the paper 'Modeling of nonlinear audio effects with end-to-end deep neural networks'

models

Models and examples built with TensorFlow

mongolian-speech-recognition

Mongolian speech recognition experiments with PyTorch

msmbuilder

:building_construction: Statistical models for biomolecular dynamics :building_construction:

msmtools

Tools for estimating and analyzing Markov state models

nara_wpe

Different implementations of "Weighted Prediction Error" for speech dereverberation

nematus

Open-Source Neural Machine Translation in Tensorflow

neon

Intel® Nervana™ reference deep learning framework committed to best performance on all hardware

neural-em

Code for the "Neural Expectation Maximization" paper.

nlp-architect

NLP Architect by Intel AI Lab: Python library for exploring the state-of-the-art deep learning topologies and techniques for natural language processing and natural language understanding

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