Thomas Ohlson Timoudas
Thomas Ohlson Timoudas
RISE Research Institutes of Sweden
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Zitiert von
Zitiert von
A study on data-driven hybrid heating load prediction methods in low-temperature district heating: An example for nursing homes in Nordic countries
Y Ding, TO Timoudas, Q Wang, S Chen, H Brattebø, N Nord
Energy Conversion and Management 269, 116163, 2022
A review of reinforcement learning for controlling building energy systems from a computer science perspective
D Weinberg, Q Wang, TO Timoudas, C Fischione
Sustainable cities and society 89, 104351, 2023
A hybrid machine learning approach for the load prediction in the sustainable transition of district heating networks
M Habib, TO Timoudas, Y Ding, N Nord, S Chen, Q Wang
Sustainable cities and society 99, 104892, 2023
Enabling Massive IoT in Ambient Backscatter Communication Systems
TO Timoudas, R Du, C Fischione
ICC 2020-2020 IEEE International Conference on Communications (ICC), 1-6, 2020
Consensus with preserved privacy against neighbor collusion
S Zhang, T Ohlson Timoudas, MA Dahleh
Control Theory and Technology 18, 409-418, 2020
Comparing backscatter communication and energy harvesting in massive IoT networks
R Du, TO Timoudas, C Fischione
IEEE Transactions on Wireless Communications 21 (1), 429-443, 2021
Sharp -Hölder continuity of the Lyapunov exponent at the bottom of the spectrum for a class of Schrödinger cocycles
JL Figueras, TO Timoudas
Discrete and continuous dynamical systems 40 (7), 4519-4531, 2020
Power law asymptotics in the creation of strange attractors in the quasi-periodically forced quadratic family
TO Timoudas
Nonlinearity 30 (12), 4483, 2017
COGNIT: Challenges and Vision for a Serverless and Multi-Provider Cognitive Cloud-Edge Continuum
P Townend, AP Martí, I De La Iglesia, N Matskanis, TO Timoudas, ...
2023 IEEE International Conference on Edge Computing and Communications …, 2023
Asymptotic laws for a class of quasi-periodic Schr\" odinger cocycles at the lowest energy of the spectrum
TO Timoudas
arXiv preprint arXiv:1809.05418, 2018
Network Consensus with Privacy: A Secret Sharing Method
S Zhang, TO Timoudas, M Dahleh
arXiv preprint arXiv:2103.03432, 2021
A novel machine learning approach to predict short-term energy load for future low-temperature district heating
TO Timoudas, Y Ding, Q Wang
CLIMA 2022 conference, 2022
A novel machine learning approach to predict short-term energy load for future low-temperature district heating
TO Timoudas, Y Ding, Q Wang
The REHVA European HVAC Journal, 19-24, 2022
Creating and Leveraging a Synthetic Dataset of Cloud Optical Thickness Measures for Cloud Detection in MSI
A Pirinen, N Abid, NA Paszkowsky, TO Timoudas, R Scheirer, ...
Remote Sensing 16 (4), 694, 2024
A General Framework to Distribute Iterative Algorithms with Localized Information over Networks
TO Timoudas, S Zhang, S Magnússon, C Fischione
IEEE Transactions on Automatic Control, 2023
Creating and Benchmarking a Synthetic Dataset for Machine Learning-Based Cloud Optical Thickness Estimation
A Pirinen, N Abid, N Agues Paszkowsky, T Ohlson Timoudas, R Scheirer, ...
EUMETSAT Meteorological Satellite Conference, 2023., 2023
Cliffhanger: An Experimental Evaluation of Stateful Serverless at the Edge
A Hasselberg, TO Timoudas, P Carbone, G Dán
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