Franziska Eckert

Personal Details

First Name:	Franziska
Middle Name:
Last Name:	Eckert
Suffix:
RePEc Short-ID:	pec68
	[This author has chosen not to make the email address public]

Affiliation

Schweizerische Nationalbank (SNB)

Bern/Zürich, Switzerland
http://www.snb.ch/
RePEc:edi:snbgvch (more details at EDIRC)

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

Sorry, no citations of working papers recorded.

Articles

1. Peter R. Wurman & Samuel Barrett & Kenta Kawamoto & James MacGlashan & Kaushik Subramanian & Thomas J. Walsh & Roberto Capobianco & Alisa Devlic & Franziska Eckert & Florian Fuchs & Leilani Gilpin & P, 2022. "Outracing champion Gran Turismo drivers with deep reinforcement learning," Nature, Nature, vol. 602(7896), pages 223-228, February.

   Cited by:

   1. Wang, Yong & Wu, Yuankai & Tang, Yingjuan & Li, Qin & He, Hongwen, 2023. "Cooperative energy management and eco-driving of plug-in hybrid electric vehicle via multi-agent reinforcement learning," Applied Energy, Elsevier, vol. 332(C).
   2. Huang, Ruchen & He, Hongwen & Gao, Miaojue, 2023. "Training-efficient and cost-optimal energy management for fuel cell hybrid electric bus based on a novel distributed deep reinforcement learning framework," Applied Energy, Elsevier, vol. 346(C).
   3. Chen, Jiaxin & Tang, Xiaolin & Wang, Meng & Li, Cheng & Li, Zhangyong & Qin, Yechen, 2025. "Enhanced applicability of reinforcement learning-based energy management by pivotal state-based Markov trajectories," Energy, Elsevier, vol. 319(C).
   4. Hu, Dong & Huang, Chao & Wu, Jingda & Wei, Henglai & Pi, Dawei, 2025. "Enhancing data-driven energy management strategy via digital expert guidance for electrified vehicles," Applied Energy, Elsevier, vol. 381(C).
   5. Matt C. Danzi & Maike F. Dohrn & Sarah Fazal & Danique Beijer & Adriana P. Rebelo & Vivian Cintra & Stephan Züchner, 2023. "Deep structured learning for variant prioritization in Mendelian diseases," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
   6. Huang, Ruchen & He, Hongwen & Su, Qicong & Wu, Jingda, 2025. "Towards sustainable and intelligent urban transportation: A novel deep transfer reinforcement learning framework for eco-driving of fuel cell buses," Energy, Elsevier, vol. 330(C).
   7. Wu, Jie & Li, Dong, 2023. "Modeling and maximizing information diffusion over hypergraphs based on deep reinforcement learning," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 629(C).
   8. Song Chen & Jiaxu Liu & Pengkai Wang & Chao Xu & Shengze Cai & Jian Chu, 2024. "Accelerated optimization in deep learning with a proportional-integral-derivative controller," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
   9. Jinming Xu & Yuan Lin, 2024. "Energy Management for Hybrid Electric Vehicles Using Safe Hybrid-Action Reinforcement Learning," Mathematics, MDPI, vol. 12(5), pages 1-20, February.
   10. Runyu Zhang & Yingjian Liu & Thomas Zheng & Sarah Eddin & Steven Nolet & Yi-Ling Liang & Shaghayegh Rezazadeh & Joseph Wilson & Hongbing Lu & Dong Qian, 2024. "A fast spatio-temporal temperature predictor for vacuum assisted resin infusion molding process based on deep machine learning modeling," Journal of Intelligent Manufacturing, Springer, vol. 35(4), pages 1737-1764, April.
   11. Nweye, Kingsley & Sankaranarayanan, Siva & Nagy, Zoltan, 2023. "MERLIN: Multi-agent offline and transfer learning for occupant-centric operation of grid-interactive communities," Applied Energy, Elsevier, vol. 346(C).
   12. Wan, He & Ruan, Jiageng & Xia, Jing & Han, Zexuan & Li, Ying, 2025. "The continuous training of machine learning-based energy management strategy for plug-in hybrid electric vehicle, part I: electric driving mode," Energy, Elsevier, vol. 333(C).
   13. Huang, Ruchen & He, Hongwen & Su, Qicong, 2024. "Towards a fossil-free urban transport system: An intelligent cross-type transferable energy management framework based on deep transfer reinforcement learning," Applied Energy, Elsevier, vol. 363(C).
   14. Chen, Jiaxin & Tang, Xiaolin & Yang, Kai, 2024. "A unified benchmark for deep reinforcement learning-based energy management: Novel training ideas with the unweighted reward," Energy, Elsevier, vol. 307(C).

More information

Research fields, statistics, top rankings, if available.

Statistics

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NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 1 paper announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.

1. NEP-AIN: Artificial Intelligence (1) 2025-11-24. Author is listed
2. NEP-BIG: Big Data (1) 2025-11-24. Author is listed
3. NEP-CMP: Computational Economics (1) 2025-11-24. Author is listed
4. NEP-FOR: Forecasting (1) 2025-11-24. Author is listed

Corrections

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