Name: Martin Ferianc
Type: User
Company: University College London
Bio: PhD student at UCL interested in machine learning and uncertainty quantification
Twitter: MartinFerianc
Location: London, UK
Website • Google Scholar • LinkedIn
Martin obtained an MEng in Electronic and Information Engineering from Imperial College London, London, UK in 2015. He is currently a PhD candidate in the Department of Electronic and Electrical Engineering at University College London. His research interests include Bayesian neural networks, deep learning , hardware acceleration and confidence calibration. He has hands-on experience from industrial/academic placements in different countries.
blockchaintutorials
This repo contains tutorials, exercises taken from an Udemy course about blockchain
c90compiler-eie2
C90 to MIPS I Compiler done as a coursework for EE2-15
combinet
ComBiNet: Compact Convolutional Bayesian Neural Network for Image Segmentation
cpusimulator-eie2
MIPS I CPU simulator done as a coursework for EE2-13
embeddedsystems-eie3
Programming and managing embedded systems done as a coursework for EE3-24
fpga-project-eie1
Implementing interactive music controls on FPGAs done as a coursework for EIE1 First Year Project
gans-eie4
Generative adversarial networks for generating numbers done as a coursework for EE4-62
hydra_plus
Simple Regularisation for Uncertainty-Aware Knowledge Distillation
imagedenoising-eie4
Image denoising done as a coursework for EE3-25
improving_per_esti_for_fpga-based_acc_for_cnns-arc2020
A codebase accompanying the paper "Improving Performance Estimation for FPGA-based Accelerators for Convolutional Neural Networks", by Ferianc et al. presented at ARC'2020
martinferianc
martinferianc.github.io
noise
Investigation of how noise perturbations impact neural network calibration and generalisation
ol-ems
Online learning algorithm for microgrid energy management based on MPC
patternrecognition-eie4
Pattern recognition techniques done as a coursework for EE4-68
pytorch-tutorial
Repository closely following the series of blog posts: Neural Network Programming - Deep Learning with PyTorch
quantised-bayesian-nets
On the Effects of Quantisation on Model Uncertainty in Bayesian Neural Networks
relax
💤 Relaxation labelling to refine edge detection 💤
renate
Library for automatic retraining and continual learning
robotics-eie3
Robotics assignments done as a coursework for CO333
sentimentanalysis-eie3
Sentiment analysis from small grayscale pictures by decision forests done as a coursework for CO395
wineclassification-eie3
Classifying wines based on physicochemical properties done as a coursework for EE3-23
yamle
YAMLE: Yet Another Machine Learning Environment
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
Django
The Web framework for perfectionists with deadlines.
Laravel
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
Microsoft
Open source projects and samples from Microsoft.
Google
Google ❤️ Open Source for everyone.
Alibaba
Alibaba Open Source for everyone
D3
Data-Driven Documents codes.
Tencent
China tencent open source team.
