LEGaTO: towards energy-efficient, secure, fault-tolerant toolset for heterogeneous computing. - Adrián Cristal; Osman S. Unsal; Xavier Martorell; Paul Carpenter; Raúl de la Cruz; Leonardo Bautista-Gomez; Daniel Jiménez-González; Carlos Álvarez 001; Behzad Salami 001; Sergi Madonar; Miquel Pericàs; Pedro Trancoso; et al. (CF, 2018)

LEGaTO: first steps towards energy-efficient toolset for heterogeneous computing. - Adrián Cristal; Osman S. Unsal; Xavier Martorell; Paul Carpenter; Raúl de la Cruz; Leonardo Bautista-Gomez; Daniel Jiménez-González; Carlos Álvarez 001; Behzad Salami 001; Sergi Madonar; Miquel Pericàs; Pedro Trancoso; et al. (SAMOS, 2018)

Design für emotional belastende Situationen. - Martin Kaiser; Fabian Koch; Kevin Häner (UP, 2019)

LEGaTO: Low-Energy, Secure, and Resilient Toolset for Heterogeneous Computing. - Behzad Salami 001; Konstantinos Parasyris; Adrián Cristal; Osman S. Unsal; Xavier Martorell; Paul Carpenter; Raúl de la Cruz; Leonardo Bautista-Gomez; Daniel A. Jiménez; Carlos Álvarez 001; S. Nabavi; Sergi Madonar; et al. (CoRR, 2019)

LEGaTO: Low-Energy, Secure, and Resilient Toolset for Heterogeneous Computing. - Behzad Salami 001; Konstantinos Parasyris; Adrián Cristal; Osman S. Unsal; Xavier Martorell; Paul Carpenter; Raúl de la Cruz; Leonardo Bautista-Gomez; Daniel A. Jiménez; Carlos Álvarez 001; Seyed Saber Nabavi Larimi; Sergi Madonar; et al. (DATE, 2020)

Accelerating Binary String Comparisons with a Scalable, Streaming-Based System Architecture Based on FPGAs. - Sarah Pilz; Florian Porrmann; Martin Kaiser; Jens Hagemeyer; James M. Hogan; Ulrich Rückert 001 (Algorithms, 2020)

Reference bias in the Illumina Isaac aligner. - Alex J. Cornish; Daniel Chubb; Anna Frangou; Phuc H. Hoang; Martin Kaiser; David C. Wedge; Richard S. Houlston (Bioinform., 2020)

VEDLIoT: Very Efficient Deep Learning in IoT. - Martin Kaiser; René Griessl; Nils Kucza; Carola Haumann; Lennart Tigges; Kevin Mika; Jens Hagemeyer; Florian Porrmann; Ulrich Rückert 001; Micha vor dem Berge; Stefan Krupop; Mario Porrmann; et al. (DATE, 2022)

VEDLIoT: Very Efficient Deep Learning in IoT. - Martin Kaiser; René Griessl; Nils Kucza; Carola Haumann; Lennart Tigges; Kevin Mika; Jens Hagemeyer; Florian Porrmann; Ulrich Rückert 001; Micha vor dem Berge; Stefan Krupop; Mario Porrmann; et al. (CoRR, 2022)

VEDLIoT: Next generation accelerated AIoT systems and applications. - Kevin Mika; René Griessl; Nils Kucza; Florian Porrmann; Martin Kaiser; Lennart Tigges; Jens Hagemeyer; Pedro Trancoso; Muhammad Waqar Azhar; Fareed Qararyah; Stavroula Zouzoula; Jämes Ménétrey; et al. (CF, 2023)

Evaluation of heterogeneous AIoT Accelerators within VEDLIoT. - René Griessl; Florian Porrmann; Nils Kucza; Kevin Mika; Jens Hagemeyer; Martin Kaiser; Mario Porrmann; Marco Tassemeier; Marcel Flottmann; Fareed Qararyah; Muhammad Waqar Azhar; Pedro Trancoso; et al. (DATE, 2023)

Reinforcement Learning for Safety Testing: Lessons from A Mobile Robot Case Study. - Tom Philip Huck; Martin Kaiser; Constantin Cronrath; Bengt Lennartson; Torsten Kröger; Tamim Asfour (CoRR, 2023)