An efficient 3D deep convolutional network for Alzheimer's disease diagnosis using MR images. - Karl Bäckström; Mahmood Nazari; Irene Yu-Hua Gu; Asgeir Store Jakola (ISBI, 2018)

MindTheStep-AsyncPSGD: Adaptive Asynchronous Parallel Stochastic Gradient Descent. - Karl Bäckström; Marina Papatriantafilou; Philippas Tsigas (IEEE BigData, 2019)

Mimir - Streaming Operators Classification with Artificial Neural Networks. - Victor Gustafsson; Hampus Nilsson; Karl Bäckström; Marina Papatriantafilou; Vincenzo Gulisano (DEBS, 2019)

Deep Learning Based Harmonics and Interharmonics Pre-Detection Designed for Compensating Significantly Time-varying EAF Currents. - Ebrahim Balouji; Karl Bäckström; Tomas McKelvey; Özgül Salor (IAS, 2019)

Controlled time series generation for automotive software-in-the-loop testing using GANs. - Dhasarathy Parthasarathy; Karl Bäckström; Jens Henriksson; Sólrún Einarsdóttir (AITest, 2020)

A Deep Learning Approach to Earth Fault Classification and Source Localization. - Ebrahim Balouji; Karl Bäckström; Petri Hovila (ISGT-Europe, 2020)

Consistent Lock-free Parallel Stochastic Gradient Descent for Fast and Stable Convergence. - Karl Bäckström; Ivan Walulya; Marina Papatriantafilou; Philippas Tsigas (IPDPS, 2021)

The Impact of Synchronization in Parallel Stochastic Gradient Descent. - Karl Bäckström; Marina Papatriantafilou; Philippas Tsigas (ICDCIT, 2022)

ASAP.SGD: Instance-based Adaptiveness to Staleness in Asynchronous SGD. - Karl Bäckström; Marina Papatriantafilou; Philippas Tsigas (ICML, 2022)

Deep Reinforcement Learning Based Grid-Forming Inverter. - Ebrahim Balouji; Karl Bäckström; Tomas McKelvey (IAS, 2023)