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Loris Di Natale
26  results:
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1

Data-driven adaptive building thermal controller tuning wit..:

Xu, Wenjie ; Svetozarevic, Bratislav ; Di Natale, Loris..
Applied Energy.  358 (2024)  - p. 122493 , 2024
Link: https://doi.org/10.1016/..
 
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2

Computationally Efficient Reinforcement Learning: Targeted ..:

, In: 2023 62nd IEEE Conference on Decision and Control (CDC),
Di Natale, Loris ; Svetozarevic, Bratislav ; Heer, Philipp. - p. 2334-2339 , 2023
Link: https://doi.org/10.1109/..
 
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3

Lessons Learned from Data-Driven Building Control Experimen..:

, In: 2022 IEEE 61st Conference on Decision and Control (CDC),
Di Natale, Loris ; Lian, Yingzhao ; Maddalena, Emilio T... - p. 1111-1117 , 2022
Link: https://doi.org/10.1109/..
 
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4

Near-optimal Deep Reinforcement Learning Policies from Data..:

, In: 2022 IEEE 17th International Conference on Control & Automation (ICCA),
Natale, Loris Di ; Svetozarevic, Bratislav ; Heer, Philipp. - p. 698-703 , 2022
Link: https://doi.org/10.1109/..
 
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5

The Potential of Vehicle-to-Grid to Support the Energy Tran..:

Di Natale, Loris ; Funk, Luca ; Rüdisüli, Martin...
Energies.  14 (2021)  16 - p. 4812 , 2021
Link: https://doi.org/10.3390/..
 
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6

Physically Consistent Neural ODEs for Learning Multi-Physic..:

Muhammad Zakwan ; Loris Di Natale ; Bratislav Svetozarevic...
info:eu-repo/grantAgreement/SNSF/Programmes - National Centres of Competence in Research (NCCRs)/51NF40_180545/.  , 2023
Link: https://zenodo.org/recor..
 
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7

The Potential of Vehicle-to-Grid to Support the Energy Tran..:

Loris Di Natale ; Luca Funk ; Martin Rüdisüli...
https://www.mdpi.com/1996-1073/14/16/4812.  , 2021
Link: https://doi.org/10.3390/..
 
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8

The Potential of Vehicle-to-Grid to Support the Energy Tran..:

Loris Di Natale ; Luca Funk ; Martin Rüdisüli...
https://dx.doi.org/10.3390/en14164812.  , 2021
Link: https://doi.org/10.3390/..
 
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9

Stable Linear Subspace Identification: A Machine Learning A..:

Di Natale, Loris ; Zakwan, Muhammad ; Svetozarevic, Bratislav...
http://arxiv.org/abs/2311.03197.  , 2023
Link: http://arxiv.org/abs/231..
 
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10

SIMBa: System Identification Methods leveraging Backpropaga..:

Di Natale, Loris ; Zakwan, Muhammad ; Heer, Philipp..
http://arxiv.org/abs/2311.13889.  , 2023
Link: http://arxiv.org/abs/231..
 
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11

Data-driven adaptive building thermal controller tuning wit..:

Xu, Wenjie ; Svetozarevic, Bratislav ; Di Natale, Loris..
http://arxiv.org/abs/2310.00758.  , 2023
Link: http://arxiv.org/abs/231..
 
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12

Lessons Learned from Data-Driven Building Control Experimen..:

Di Natale, Loris ; Lian, Yingzhao ; Maddalena, Emilio T..
http://arxiv.org/abs/2205.15703.  , 2022
Link: http://arxiv.org/abs/220..
 
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13

Towards Scalable Physically Consistent Neural Networks: an ..:

Di Natale, Loris ; Svetozarevic, Bratislav ; Heer, Philipp.
http://arxiv.org/abs/2212.12380.  , 2022
Link: http://arxiv.org/abs/221..
 
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14

Physically Consistent Neural Networks for building thermal ..:

Di Natale, Loris ; id_orcid:0 000-0002-3295-412X
http://hdl.handle.net/20.500.11850/531880.  , 2022
Link: https://hdl.handle.net/2..
 
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15

Near-optimal Deep Reinforcement Learning Policies from Data..:

Di Natale, Loris ; Svetozarevic, Bratislav ; Heer, Philipp.
http://arxiv.org/abs/2203.05434.  , 2022
Link: http://arxiv.org/abs/220..
 
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