10 citations · 14 across the 5 of their papers we have counts for
5 papers
Denoising Diffusion Probabilistic Models as a Defense against Adversarial Attacks
Lars Lien Ankile, Anna Midgley, Sebastian Weisshaar
Neural Networks are infamously sensitive to small perturbations in their inputs, making them vulnerable to adversarial attacks. This project evaluates the performance of Denoising…
Deep Learning and Linear Programming for Automated Ensemble Forecasting and Interpretation
Lars Lien Ankile, Kjartan Krange
This paper presents an ensemble forecasting method that shows strong results on the M4 Competition dataset by decreasing feature and model selection assumptions, termed DONUT (DO N…
Deep Convolutional Neural Networks: A survey of the foundations, selected improvements, and some current applications
Lars Lien Ankile, Morgan Feet Heggland, Kjartan Krange
Within the world of machine learning there exists a wide range of different methods with respective advantages and applications. This paper seeks to present and discuss one such me…
Application of Facial Recognition using Convolutional Neural Networks for Entry Access Control
Lars Lien Ankile, Morgan Feet Heggland, Kjartan Krange
The purpose of this paper is to design a solution to the problem of facial recognition by use of convolutional neural networks, with the intention of applying the solution in a cam…
Approximate Strategyproofness in Large, Two-Sided Matching Markets
Lars Lien Ankile, Kjartan Krange, Yuto Yagi
An approximation of strategyproofness in large, two-sided matching markets is highly evident. Through simulations, one can observe that the percentage of agents with useful deviati…