Department of Information Technology


  • (Apr2020) Antônio H. Ribeiro, Horta Ribeiro, Gabriela M. M. Paixão, Derick M. Oliveira, Paulo R. Gomes, Jéssica A. Canazartand, Milton P. S. Ferreira, Carl R. Andersson, Peter W. Macfarlane, Wagner Meira, Thomas B. Schön and Antonio Luiz P. Ribeiro. Automatic Diagnosis of the Short-Duration 12-Lead ECG using a Deep Neural Network the CODE Study. In Nature Communications. 2020 ArXiv Nature Communications
  • (Dec2020) Carl Andersson, Antônio H. Ribeiro, Koen Tiels, Niklas Wahlström and Thomas B. Schön. Deep convolutional networks in system identification. In: Proceedings of the IEEE 58th IEEE Conference on Decision and Control (CDC). Nice, France, 2019 ArXiv
  • (Apr2019) Juozas Vaicenavicius, David Widmann, Carl Andersson, Fredrik Lindsten, Jakob Roll and Thomas Schön. Evaluating model calibration in classification. In: Proceedings of Machine Learning Research. Naha, Japan, 2019 ArXiv
  • (Jul2018) Carl Andersson, Niklas Wahlström and Thomas B. Schön. Data-Driven Impulse Response Regularization via Deep Learning. In Proceedings of 18th IFAC Symposium on System Identification (SYSID), Stockholm, Sweden, 2018. ArXiv
  • (Oct2013) Mats Elfving, Carl Andersson, Joakim Hägvall and Olov Wilander, Enhanced methods for warping, edge blending and colour correction when projecting in domes, Proceedings of the 4:th CEAS conference. Linköping, 2013 PDF
  • (Sep2013) Carl Andersson, Seamless Automatic Projector Calibration of Large Immersive Displays using Gray Code, Master Thesis PDFDiVA

Work in progress


  • (Nov2019) Deep sequential models NewLeads seminar at KTH pdf
Updated  2020-05-31 11:00:19 by Carl Andersson.