164 citations · 413 across the 15 of their papers we have counts for
5 papers · 1 filter
Information Plane Analysis of Deep Neural Networks via Matrix-Based Renyi's Entropy and Tensor Kernels
Kristoffer Wickstrøm, Sigurd Løkse, Michael Kampffmeyer +3
Analyzing deep neural networks (DNNs) via information plane (IP) theory has gained tremendous attention recently as a tool to gain insight into, among others, their generalization…
Road Mapping In LiDAR Images Using A Joint-Task Dense Dilated Convolutions Merging Network
Qinghui Liu, Michael Kampffmeyer, Robert Jenssen +1
It is important, but challenging, for the forest industry to accurately map roads which are used for timber transport by trucks. In this work, we propose a Dense Dilated Convolutio…
Dense Dilated Convolutions Merging Network for Semantic Mapping of Remote Sensing Images
Qinghui Liu, Michael Kampffmeyer, Robert Jenssen +1
We propose a network for semantic mapping called the Dense Dilated Convolutions Merging Network (DDCM-Net) to provide a deep learning approach that can recognize multi-scale and co…
Learning Latent Representations of Bank Customers With The Variational Autoencoder
Rogelio A Mancisidor, Michael Kampffmeyer, Kjersti Aas +1
Learning data representations that reflect the customers' creditworthiness can improve marketing campaigns, customer relationship management, data and process management or the cre…
Deep Divergence-Based Approach to Clustering
Michael Kampffmeyer, Sigurd Løkse, Filippo M. Bianchi +3
A promising direction in deep learning research consists in learning representations and simultaneously discovering cluster structure in unlabeled data by optimizing a discriminati…