Preventive maintenance scheduling of multi-component systems with interval costs. - Emil Gustavsson; Michael Patriksson; Ann-Brith Strömberg; Adam Wojciechowski; Magnus Önnheim (Comput. Ind. Eng., 2014)

Scheduling tamping operations on railway tracks using mixed integer linear programming. - Emil Gustavsson (EURO J. Transp. Logist., 2015)

Primal convergence from dual subgradient methods for convex optimization. - Emil Gustavsson; Michael Patriksson; Ann-Brith Strömberg (Math. Program., 2015)

Learning to Play Guess Who? and Inventing a Grounded Language as a Consequence. - Emilio Jorge; Mikael Kågebäck; Emil Gustavsson (CoRR, 2016)

Contraction Clustering (Raster) - A Big Data Algorithm for Density-Based Clustering in Constant Memory and Linear Time. - Gregor Ulm; Emil Gustavsson; Mats Jirstrand (MOD, 2017)

Ergodic, primal convergence in dual subgradient schemes for convex programming, II: the case of inconsistent primal problems. - Magnus Önnheim; Emil Gustavsson; Ann-Brith Strömberg; Michael Patriksson; Torbjörn Larsson (Math. Program., 2017)

A Performance Evaluation of Federated Learning Algorithms. - Adrian Nilsson; Simon Smith 005; Gregor Ulm; Emil Gustavsson; Mats Jirstrand (DIDL@Middleware, 2018)

Functional Federated Learning in Erlang (ffl-erl). - Gregor Ulm; Emil Gustavsson; Mats Jirstrand (WFLP, 2018)

Active-Code Replacement in the OODIDA Data Analytics Platform. - Gregor Ulm; Emil Gustavsson; Mats Jirstrand (Euro-Par Workshops, 2019)

Reinforcement Learning Informed by Optimal Control. - Magnus Önnheim; Pontus Andersson; Emil Gustavsson; Mats Jirstrand (ICANN (Workshop), 2019)

Architecture-Aware Bayesian Optimization for Neural Network Tuning. - Anders Sjöberg; Magnus Önnheim; Emil Gustavsson; Mats Jirstrand (ICANN (2), 2019)

Federated Learning of Deep Neural Decision Forests. - Anders Sjöberg; Emil Gustavsson; Ashok Chaitanya Koppisetty; Mats Jirstrand (LOD, 2019)

OODIDA: On-board/Off-board Distributed Data Analytics for Connected Vehicles. - Gregor Ulm; Emil Gustavsson; Mats Jirstrand (CoRR, 2019)

Contraction Clustering (RASTER): A Very Fast Big Data Algorithm for Sequential and Parallel Density-Based Clustering in Linear Time, Constant Memory, and a Single Pass. - Gregor Ulm; Simon Smith 005; Adrian Nilsson; Emil Gustavsson; Mats Jirstrand (CoRR, 2019)

Facilitating rapid prototyping in the distributed data analytics platform OODIDA via active-code replacement. - Gregor Ulm; Simon Smith 005; Adrian Nilsson; Emil Gustavsson; Mats Jirstrand (Array, 2020)

S-RASTER: contraction clustering for evolving data streams. - Gregor Ulm; Simon Smith 005; Adrian Nilsson; Emil Gustavsson; Mats Jirstrand (J. Big Data, 2020)

Natural language processing methods for knowledge management - Applying document clustering for fast search and grouping of engineering documents. - Ivar Örn Arnarsson; Otto Frost; Emil Gustavsson; Mats Jirstrand; Johan Malmqvist (Concurr. Eng. Res. Appl., 2021)

OODIDA: On-Board/Off-Board Distributed Real-Time Data Analytics for Connected Vehicles. - Gregor Ulm; Simon Smith 005; Adrian Nilsson; Emil Gustavsson; Mats Jirstrand (Data Sci. Eng., 2021)

Model Predictive Control when utilizing LSTM as dynamic models. - Marvin Jung; Paulo Renato da Costa Mendes; Magnus Önnheim; Emil Gustavsson (Eng. Appl. Artif. Intell., 2023)