activity
20182024
most citedIndoor environment data time-series reconstruction using autoencoder neural networks

44 citations · 114 across the 10 of their papers we have counts for

collaborators

11 papers

cs.LG2024★ 7 cited

Spatial features of CO2 for occupancy detection in a naturally ventilated school building

Qirui Huang, Marc Syndicus, Jérôme Frisch +1

Accurate occupancy information helps to improve building energy efficiency and occupant comfort. Occupancy detection methods based on CO2 sensors have received attention due to the…

stat.ML2023★ 19 cited

Opening the Black Box: Towards inherently interpretable energy data imputation models using building physics insight

Antonio Liguori, Matias Quintana, Chun Fu +3

Missing data are frequently observed by practitioners and researchers in the building energy modeling community. In this regard, advanced data-driven solutions, such as Deep Learni…

cs.CV2021★ 7 cited

IFCNet: A Benchmark Dataset for IFC Entity Classification

Christoph Emunds, Nicolas Pauen, Veronika Richter +2

Enhancing interoperability and information exchange between domain-specific software products for BIM is an important aspect in the Architecture, Engineering, Construction and Oper…

stat.ML2020★ 44 cited

Indoor environment data time-series reconstruction using autoencoder neural networks

Antonio Liguori, Romana Markovic, Thi Thu Ha Dam +3

As the number of installed meters in buildings increases, there is a growing number of data time-series that could be used to develop data-driven models to support and optimize bui…

cs.CY2018

Learning short-term past as predictor of human behavior in commercial buildings

Romana Markovic, Jérôme Frisch, Christoph van Treeck

This paper addresses the question of identifying the time-window in short-term past from which the information regarding the future occupant's window opening actions and resulting…

cs.PF2018★ 8 cited

Design and optimisation of an efficient HDF5 I/O kernel for massive parallel fluid flow simulations

Christoph Ertl, Jérôme Frisch, Ralf-Peter Mundani

More and more massive parallel codes running on several hundreds of thousands of cores enter the computational science and engineering domain, allowing high-fidelity computations o…

cs.CE2018★ 6 cited

Computational steering of complex flow simulations

Atanas Atanasov, Hans-Joachim Bungartz, Jérôme Frisch +4

Computational Steering, the combination of a simulation back-end with a visualisation front-end, offers great possibilities to exploit and optimise scenarios in engineering applica…

cs.LG2018

Window Opening Model using Deep Learning Methods

Romana Markovic, Eva Grintal, Daniel Wölki +2

Occupant behavior (OB) and in particular window openings need to be considered in building performance simulation (BPS), in order to realistically model the indoor climate and ener…

cs.CE2018★ 2 cited

Interactive data exploration for high-performance fluid flow computations through porous media

Nevena Perović, Jérôme Frisch, Ralf-Peter Mundani +1

Huge data advent in high-performance computing (HPC) applications such as fluid flow simulations usually hinders the interactive processing and exploration of simulation results. S…

cs.PF2018★ 3 cited

Measuring and comparing the scaling behaviour of a high-performance CFD code on different supercomputing infrastructures

Jérôme Frisch, Ralf-Peter Mundani

Parallel code design is a challenging task especially when addressing petascale systems for massive parallel processing (MPP), i.e. parallel computations on several hundreds of tho…

cs.CE2018★ 18 cited

A sliding window technique for interactive high-performance computing scenarios

Ralf-Peter Mundani, Jérôme Frisch, Vasco Varduhn +1

Interactive high-performance computing is doubtlessly beneficial for many computational science and engineering applications whenever simulation results should be visually processe…