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Philipp Geyer
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2020 – today
- 2024
- [j15]Xia Chen
, Xiangbin Teng
, Han Chen, Yafeng Pan
, Philipp Geyer
:
Toward reliable signals decoding for electroencephalogram: A benchmark study to EEGNeX. Biomed. Signal Process. Control. 87(Part B): 105475 (2024) - [j14]Xia Chen
, Manav Mahan Singh, Philipp Geyer:
Utilizing domain knowledge: Robust machine learning for building energy performance prediction with small, inconsistent datasets. Knowl. Based Syst. 294: 111774 (2024) - [i9]Xia Chen, Alexander Rex, Janis Woelke, Christoph Eckert, Boris Bensmann, Richard Hanke-Rauschenbach, Philipp Geyer:
Machine Learning in Proton Exchange Membrane Water Electrolysis - Part I: A Knowledge-Integrated Framework. CoRR abs/2404.03660 (2024) - 2023
- [i8]Xia Chen
, Xiaoye Cai, Alexander Kümpel, Dirk Müller, Philipp Geyer:
A Dynamic Feedforward Control Strategy for Energy-efficient Building System Operation. CoRR abs/2302.10179 (2023) - [i7]Xia Chen
, Manav Mahan Singh, Philipp Geyer:
Utilizing Domain Knowledge: Robust Machine Learning for Building Energy Prediction with Small, Inconsistent Datasets. CoRR abs/2302.10784 (2023) - [i6]Xia Chen, Philipp Geyer:
Pathway toward prior knowledge-integrated machine learning in engineering. CoRR abs/2307.06950 (2023) - [i5]Xia Chen, Ruiji Sun, Ueli Saluz, Stefano Schiavon, Philipp Geyer:
Using causal inference to avoid fallouts in data-driven parametric analysis: a case study in the architecture, engineering, and construction industry. CoRR abs/2309.11509 (2023) - 2022
- [j13]Xia Chen
, Tong Guo, Martin Kriegel
, Philipp Geyer:
A hybrid-model forecasting framework for reducing the building energy performance gap. Adv. Eng. Informatics 52: 101627 (2022) - [i4]Xia Chen
, Jimmy Abualdenien, Manav Mahan Singh, André Borrmann
, Philipp Geyer:
Introducing causal inference in the energy-efficient building design process. CoRR abs/2203.10115 (2022) - [i3]Xia Chen
, Tong Guo, Martin Kriegel
, Philipp Geyer:
A hybrid-model approach for reducing the performance gap in building energy forecasting. CoRR abs/2206.00460 (2022) - [i2]Xia Chen
, Xiangbin Teng
, Han Chen, Yafeng Pan, Philipp Geyer:
Toward reliable signals decoding for electroencephalogram: A benchmark study to EEGNeX. CoRR abs/2207.12369 (2022) - 2021
- [j12]Philipp Geyer
, Christian Koch, Pieter Pauwels:
Fusing data, engineering knowledge and artificial intelligence for the built environment. Adv. Eng. Informatics 48: 101242 (2021) - [i1]Philipp Geyer
, Manav Mahan Singh, Xia Chen:
Explainable AI for engineering design: A unified approach of systems engineering and component-based deep learning. CoRR abs/2108.13836 (2021) - 2020
- [j11]Manav Mahan Singh, Philipp Geyer
:
Information requirements for multi-level-of-development BIM using sensitivity analysis for energy performance. Adv. Eng. Informatics 43: 101026 (2020) - [j10]Manav Mahan Singh, Sundaravelpandian Singaravel, Ralf Klein, Philipp Geyer
:
Quick energy prediction and comparison of options at the early design stage. Adv. Eng. Informatics 46: 101185 (2020) - [j9]Jimmy Abualdenien, Patricia Schneider-Marin, Ata Zahedi, Hannes Harter, Hannah Exner, Daniel Steiner, Manav Mahan Singh, André Borrmann, Werner Lang, Frank Petzold, Markus König, Philipp Geyer, Martina Schnellenbach-Held:
Consistent management and evaluation of building models in the early design stages. J. Inf. Technol. Constr. 25: 212-232 (2020)
2010 – 2019
- 2019
- [j8]Sundaravelpandian Singaravel, Johan A. K. Suykens
, Philipp Geyer
:
Deep convolutional learning for general early design stage prediction models. Adv. Eng. Informatics 42 (2019) - [e1]Philipp Geyer, Karen Allacker, Mattias Schevenels, Frank De Troyer, Pieter Pauwels:
26th International Workshop on Intelligent Computing in Engineering, EG-ICE 2019, Leuven, Belgium, June 30 - July 3, 2019. CEUR Workshop Proceedings 2394, CEUR-WS.org 2019 [contents] - 2018
- [j7]Sundaravelpandian Singaravel, Johan A. K. Suykens
, Philipp Geyer
:
Deep-learning neural-network architectures and methods: Using component-based models in building-design energy prediction. Adv. Eng. Informatics 38: 81-90 (2018) - [c2]Philipp Geyer
, Manav Mahan Singh, Sundaravelpandian Singaravel:
Component-Based Machine Learning for Energy Performance Prediction by MultiLOD Models in the Early Phases of Building Design. EG-ICE 2018: 516-534 - [c1]Manav Mahan Singh, Philipp Geyer:
Statistical Decision Assistance for Determining Energy-Efficient Options In Building Design Under Uncertainty. EG-ICE 2018 - 2017
- [j6]Philipp Geyer
, Arno Schlueter
, Sasha Cisar
:
Application of clustering for the development of retrofit strategies for large building stocks. Adv. Eng. Informatics 31: 32-47 (2017) - 2016
- [j5]Arno Schlueter
, Philipp Geyer
, Sasha Cisar
:
Analysis of Georeferenced Building Data for the Identification and Evaluation of Thermal Microgrids. Proc. IEEE 104(4): 713-725 (2016) - 2014
- [j4]Philipp Geyer
, Jochen Stopper, Werner Lang
, Maximilian Thumfart:
A Systems Engineering Methodology for Designing and Planning the Built Environment - Results from the Urban Research Laboratory Nuremberg and Their Integration in Education. Syst. 2(2): 137-158 (2014) - 2013
- [j3]André Borrmann
, Philipp Geyer
, Christian Koch
:
Advanced computing for the built environment. Adv. Eng. Informatics 27(4): 411-412 (2013) - 2012
- [j2]Philipp Geyer
:
Systems modelling for sustainable building design. Adv. Eng. Informatics 26(4): 656-668 (2012) - 2010
- [b1]Philipp Geyer:
Multidisziplinäre Entwurfsoptimierung für das Bauwesen (Multidisciplinary Design Optimization for Buidlings). TU Berlin, Germany, 2010
2000 – 2009
- 2009
- [j1]Philipp Geyer
:
Component-oriented decomposition for multidisciplinary design optimization in building design. Adv. Eng. Informatics 23(1): 12-31 (2009)
Coauthor Index
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last updated on 2024-06-10 21:26 CEST by the dblp team
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