Karl Bäckström

Showing 13 publications

2023

Deep Reinforcement Learning Based Grid-Forming Inverter

Ebrahim Balouji, Karl Bäckström, Tomas McKelvey
2023 IEEE Industry Applications Society Annual Meeting, IAS 2023
Paper in proceeding
2022

The Impact of Synchronization in Parallel Stochastic Gradient Descent

Karl Bäckström, Marina Papatriantafilou, Philippas Tsigas
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 13145 LNCS, p. 60-75
Paper in proceeding
2022

ASAP.SGD: Instance-based Adaptiveness to Staleness in Asynchronous SGD

Karl Bäckström, Marina Papatriantafilou, Philippas Tsigas
Proceedings of Machine Learning Research. Vol. PMLR 162, p. 1261-1271
Paper in proceeding
2021

Consistent lock-free parallel stochastic gradient descent for fast and stable convergence

Karl Bäckström, Ivan Walulya, Marina Papatriantafilou et al
Proceedings - 2021 IEEE 35th International Parallel and Distributed Processing Symposium, IPDPS 2021, p. 423-432
Paper in proceeding
2020

A deep learning approach to earth fault classification and source localization

Ebrahim Balouji, Karl Bäckström, Petri Hovila
IEEE PES Innovative Smart Grid Technologies Conference Europe. Vol. 2020-October, p. 635-639
Paper in proceeding
2020

Deep-Learning-Based Harmonics and Interharmonics Predetection Designed for Compensating Significantly Time-Varying EAF Currents

Ebrahim Balouji, Karl Bäckström, Tomas McKelvey et al
IEEE Transactions on Industry Applications. Vol. 56 (3), p. 3250-3260
Journal article
2020

Controlled time series generation for automotive software-in-the-loop testing using GANs

Dhasarathy Parthasarathy, Karl Bäckström, Jens Henriksson et al
Proceedings - 2020 IEEE International Conference on Artificial Intelligence Testing, AITest 2020, p. 39-46
Paper in proceeding
2019

Deep Learning Based Harmonics and Interharmonics Pre-Detection Designed for Compensating Significantly Time-varying EAF Currents

Ebrahim Balouji, Karl Bäckström, Tomas McKelvey et al
2019 IEEE Industry Applications Society Annual Meeting, IAS 2019
Paper in proceeding
2019

MindTheStep-AsyncPSGD: Adaptive Asynchronous Parallel Stochastic Gradient Descent

Karl Bäckström, Marina Papatriantafilou, Philippas Tsigas
Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019, p. 16-25
Paper in proceeding
2019

Mimir - Streaming operators classification with artificial neural networks

Victor Gustafsson, Hampus Nilsson, Karl Bäckström et al
DEBS 2019 - Proceedings of the 13th ACM International Conference on Distributed and Event-Based Systems, p. 258-259
Paper in proceeding
2018

An efficient 3D deep convolutional network for Alzheimer's disease diagnosis using MR images

Karl Bäckström, Mahmood Nazari, Irene Yu-Hua Gu et al
, p. 149-153
Paper in proceeding

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Showing 1 research projects

2018–2023

WASP SAS: Structuring data for continuous processing and ML systems

Marina Papatriantafilou Networks and Systems (Chalmers)
Vincenzo Massimiliano Gulisano Networks and Systems (Chalmers)
Karl Bäckström Networks and Systems (Chalmers)
Philippas Tsigas Networks and Systems (Chalmers)
Wallenberg AI, Autonomous Systems and Software Program

9 publications exist
There might be more projects where Karl Bäckström participates, but you have to be logged in as a Chalmers employee to see them.