
OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!
If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.
Requested Article:
An innovative heterogeneous transfer learning framework to enhance the scalability of deep reinforcement learning controllers in buildings with integrated energy systems
Davide Coraci, Silvio Brandi, Tianzhen Hong, et al.
Building Simulation (2024) Vol. 17, Iss. 5, pp. 739-770
Open Access | Times Cited: 9
Davide Coraci, Silvio Brandi, Tianzhen Hong, et al.
Building Simulation (2024) Vol. 17, Iss. 5, pp. 739-770
Open Access | Times Cited: 9
Showing 9 citing articles:
A scalable approach for real-world implementation of deep reinforcement learning controllers in buildings based on online transfer learning: the HiLo case study
Davide Coraci, Alberto Silvestri, Giuseppe Razzano, et al.
Energy and Buildings (2025) Vol. 329, pp. 115254-115254
Open Access | Times Cited: 1
Davide Coraci, Alberto Silvestri, Giuseppe Razzano, et al.
Energy and Buildings (2025) Vol. 329, pp. 115254-115254
Open Access | Times Cited: 1
Real building implementation of a deep reinforcement learning controller to enhance energy efficiency and indoor temperature control
Alberto Silvestri, Davide Coraci, Silvio Brandi, et al.
Applied Energy (2024) Vol. 368, pp. 123447-123447
Open Access | Times Cited: 11
Alberto Silvestri, Davide Coraci, Silvio Brandi, et al.
Applied Energy (2024) Vol. 368, pp. 123447-123447
Open Access | Times Cited: 11
Transfer Learning with TD3 for Adaptive HVAC Control in Diverse Building Environments
Kevlyn Kadamala, Des Chambers, Enda Barrett
Communications in computer and information science (2025), pp. 256-267
Closed Access
Kevlyn Kadamala, Des Chambers, Enda Barrett
Communications in computer and information science (2025), pp. 256-267
Closed Access
Enabling efficient cross-building HVAC fault inferences through novel unsupervised domain adaptation methods
Yutian Lei, Cheng Fan, Haihui He, et al.
Building and Environment (2025), pp. 112678-112678
Closed Access
Yutian Lei, Cheng Fan, Haihui He, et al.
Building and Environment (2025), pp. 112678-112678
Closed Access
A novel temporal domain adaptation framework for residential electricity consumption forecasting under incomplete information
Sheng Li, Xiaoxiao Xu, Yadong Xu, et al.
Energy and Buildings (2025), pp. 115513-115513
Closed Access
Sheng Li, Xiaoxiao Xu, Yadong Xu, et al.
Energy and Buildings (2025), pp. 115513-115513
Closed Access
Practical deployment of reinforcement learning for building controls using an imitation learning approach
Alberto Silvestri, Davide Coraci, Silvio Brandi, et al.
Energy and Buildings (2025), pp. 115511-115511
Open Access
Alberto Silvestri, Davide Coraci, Silvio Brandi, et al.
Energy and Buildings (2025), pp. 115511-115511
Open Access
Deep reinforcement learning control for co-optimizing energy consumption, thermal comfort, and indoor air quality in an office building
Fangzhou Guo, Sang woo Ham, Donghun Kim, et al.
Applied Energy (2024) Vol. 377, pp. 124467-124467
Closed Access | Times Cited: 1
Fangzhou Guo, Sang woo Ham, Donghun Kim, et al.
Applied Energy (2024) Vol. 377, pp. 124467-124467
Closed Access | Times Cited: 1
Advances in smart cities with system integration and energy digitalization technologies: A state-of-the-art review
Jiashu Kong, Yitong Dong, Z F Zhang, et al.
Sustainable Energy Technologies and Assessments (2024) Vol. 72, pp. 104012-104012
Closed Access
Jiashu Kong, Yitong Dong, Z F Zhang, et al.
Sustainable Energy Technologies and Assessments (2024) Vol. 72, pp. 104012-104012
Closed Access
Enhancing Energy Efficiency and Flexibility in Educational Buildings Through a Deep Reinforcement Learning-Based Controller for Rooftop Units
Silvio Brandi, Andrea Pizza, Giacomo Buscemi, et al.
Lecture notes in civil engineering (2024), pp. 51-57
Closed Access
Silvio Brandi, Andrea Pizza, Giacomo Buscemi, et al.
Lecture notes in civil engineering (2024), pp. 51-57
Closed Access