CONFERENCES

Conferences

  • oral presentations

  • poster presentations

2024

2024

2023

2023

  • T. Kirschbaum, B. von Seggern, J. Dzubiella, A. Bande, and F. Noé. Machine Learning Frontier Orbital Energies of Nanodiamonds. (Oral presentation), Asia Pacific Conference of Theoretical and Computational Chemistry, Quy Nhon, Vietnam, 19-23 February 2023.
  • K. Singh. Machine Learning for Quantum Dynamics. (Oral presentation), Asia Pacific Conference of Theoretical and Computational Chemistry, Quy Nhon, Vietnam, 19-23 February 2023.
  • D. Collin, S. Bianco, G. Gallego, Y. Shprits. Forecasting solar wind speed from solar EUV images. (Oral and poster presentation), International Workshop on Machine Learning and Computer Vision in Heliophysics, Sofia, Bulgaria, 19-21 April 2023.
  • B. Groenke, M. Langer, G. Gallego, and J. Boike. Exploring physics-informed machine learning for accelerated simulation of permafrost processes. (Oral presentation), EGU General Assembly, Vienna, Austria, 24–28 April 2023. https://doi.org/10.5194/egusphere-egu23-10135
  • D. Collin, S. Bianco, G. Gallego, and Y. Shprits. Forecasting solar wind speed by machine learning based on coronal hole characteristics. (Poster presentation), EGU General Assembly , Vienna, Austria, 24–28 April 2023. https://doi.org/10.5194/egusphere-egu23-6968
  • V. Döpper, R. Jackisch, J. Gloy, T. Rettelbach, J. Boike, …, G. Grosse, and S. Kruse. Towards an automatic segmentation and classification of multi-source point clouds for Arctic to boreal permafrost ecosystem analysis. (Poster presentation), EGU General Assembly, Vienna, Austria, 24–28 April, 2023. https://doi.org/10.5194/egusphere-egu23-15600
  • N. Veigel, H. Kreibich, J.A. de Bruijn, J.C.J.H. Aerts, and A. Cominola. A Transformer-Based Analysis of Tweets in Germany to Investigate the Appearance and Evolution of the 2021 Eifel Flood in Social Media. (Poster presentation), EGU General Assembly, Vienna, Austria, 24–28 April 2023. https://doi.org/10.5194/egusphere-egu23-6038
  • D. Collin, S. Bianco, G. Gallego, and Y. Shprits. Forecasting solar wind speed from solar EUV images. (Oral presentation), IUGG General Assembly, Berlin, Germany, 11-20 July 2023. https://doi.org/10.57757/IUGG23-2070
  • B. Groenke, M. Langer, J. Nitzbon, S. Westermann, G. Gallego, and J. Boike. Explaining uncertainty in the thermal state of permafrost with Bayesian inversion of hydrothermal dynamics. (Oral presentation), 6th European Conference on Permafrost, Puigcerdà, Catalonia, Spain, 18-22 June 2023.
  • B. Groenke, M. Langer, G. Gallego, and J. Boike. Applications of physic-informed machine learning in accelerating dynamical models of permafrost processes. (Oral presentation), IUGG23 General Assembly, Berlin, Germany, 11-20 July, 2023.
  • H. Lilienkamp, R. Bossu, F. Cotton, F. Finazzi, G. Weatherill, and S. von Spech. Utilization of crowdsourced macroseismic observations to distinguish “high-impact” from “low-impact” earthquakes globally within minutes of an event. (Oral presentation), IUGG23 General Assembly, Berlin, Germany, 11-20 July 2023.
  • V. Döpper et al. Unlocking the Potential of Arctic to Boreal Multi-Source Point Clouds: Deep and Transfer Learning for Automated Segmentation and Classification. (Poster presentation), SilviLaser 2023, London, UK, 6-8 September, 2023.
  • J. Schaible, B. Nouri, T. Kotzab, M. Loevenich, N. Blum, A. Hammer, K. Jäger, C. Becker, and S. Wilbert. Application of Nowcasting to Reduce the Impact of Irradiance Ramps on PV Power Plants. (Oral presentation), EU PVSEC, Lisbon, Portugal, 18-22 September 2023.
  • T. Rettelbach, K. Heidler, N. Lehmann, I. Nitze, M. Langer, X. Zhu, J-C. Freytag, G. Grosse, and D. Kainmüller. Cross-resolution image segmentation for mapping smallest ponds in the Arctic. (Poster presentation), AI4EO Symposium 2023, Munich, Germany, 9-10 October 2023.
  • A. Mehta. Machine Learning for Imaging Atmospheric Cherenkov Telescope (IACT) Background Rejection. H.E.S.S. Collaboration Meeting, Bordeaux, France, 24-29 September 2023.
  • V. Huryn, R. Monti, A.A. Rakowski, and V. Döring. Disentanglement learning for functional genomics data. (Poster presentation), Kipoi Summit. New Horizons in Computational Regulatory Genomics. Zugspitze, Germany, 25-26 September 2023.
  • M. Schubach, T. Maass, L. Nazaretyan, S. Röner, and M. Kircher. CADD v1.7: Using protein language models, regulatory CNNs and other nucleotide-level scores to improve genome-wide variant predictions. (Poster presentation), Genome Informatics, Cold Spring Harbour, 6-9 December 2023.
  • D. Collin, S. Bianco, G. Gallego, and Y. Shprits. Forecasting solar wind speed from coronal holes. (Oral presentation), AGU Fall Meeting, San Francisco, USA, 11–15 December 2023.

2022

2022

  • P. Graniero. Comparison of Unsupervised Algorithms for PV Fault Detection, and Data Sources for Power Nowcasting. (Oral presentation), Cost Action Pearl PV’s Conference- Enabling the Terawatt Transition,  Enschede, The Netherlands, 14-16 March 2022.

  • T. Rettelbach, I. Nitze, and G. Grosse. Polar-6 airborne expedition Perma-X West Alaska 2021. (Oral presentation), 12. Treffen des AK Permafrost der DGP, Online, 6 May 2022.

  • T. Rettelbach, I. Nitze, S. Schäffler, S. Barth, I. Grünberg, J. Hammar, M. Gessner, T. Bucher, J. Brauchle, T. Sachs, J. Boike, and G. Grosse. Super-high-resolution Earth observation datasets of North American permafrost landscapes. (Oral and poster presentation), 8th NASA ABoVE Science Team Meeting, Fairbanks, Alaska, USA, 9-12 May 2022.

  • B. Groenke, F. Miesner, M. Langer, G. Gallego and J. Boike. An energy conserving method for simulating heat transfer in permafrost with hybrid modeling. (Oral presentation), Climate Informatics 2022, Online, 9-13 May 2022.

  • T. Rettelbach, C. Witharana, A. Liljedahl, M. Langer, I. Nitze, J-C. Freytag, and G. Grosse. The Evolution of ice-wedge polygon networks in tundra fire scars. (Poster presentation), 16th International Circumpolar Remote Sensing Symposium, Fairbanks, Alaska, USA, 16-20 May 2022.

  • T. Rettelbach, M. Langer, I. Nitze, V. Helm, J-C. Freytag, and G. Grosse. Quantifying rapid permafrost thaw with computer vision and graph theory. (Poster presentation), ESA Living Planet Symposium, Bonn, Germany, 23-27 May 2022. 

  • B. Ghosh, M. Motagh, S. Garg, M. Sips, D. Eggert. Deep learning, remote sensing and visual analytics to support automatic flood detection. (Oral presentation), EGU General Assembly, Vienna, Austria / Online, 23-27 May 2022.

  • N. Veigel, H. Kreibich, and A. Cominola. Exploring Behavioral Determinants of Flood Insurance Adoption with Explainable Machine Learning in the Continental US. EGU General Assembly, Vienna, Austria / Online, 23-27 May 2022. https://doi.org/10.5194/egusphere-egu22-5839

  • G. Pfalz, B. Diekmann, J-C. Freytag, L. Syrykh, D.A. Subetto, and B. K.  Biskaborn, Using LANDO as a universal wrapper for applying multiple age-depth modeling systems for sediment records from Arctic lake systems. EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022. https://doi.org/10.5194/egusphere-egu22-8743

  • J. Münchmeyer, J. Woollam, F. Tilmann, A. Rietbrock, D. Lange, ..., and H. Soto. Which picker fits my data? A quantitative evaluation of deep learning based seismic pickers. EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022.  https://meetingorganizer.copernicus.org/EGU22/EGU22-4071.html

  • B. Groenke, M. Langer, G. Gallego and J. Boike. A probabilistic analysis of permafrost temperature trends with ensemble modeling of heat transfer. (PICO presentation), EGU General Assembly, Vienna, Austria, 23–27 May 2022. https://doi.org/10.5194/egusphere-egu22-10509

  • K. Styp-Rekowski, I. Michaelis, C. Stolle, and O. Kao. Magnetic Datasets from Non-dedicated Satellites. (Oral Presentation), Living Planet Symposium, Bonn, Germany, 23-27 May 2022.

  • H. Stolte, J. Sinapius, I. Sadeh, E. Pueschel, D. Berge, M. Weidlich. Detecting VHE blazar flares with deep learning. (Oral presentation), International Conference on Machine Learning for Astrophysics - ML4Astro, Catania, Italy, 30 May - 2 June 2022.

  • P. Tillmann, K. Jäger, A. Karsenti, L. Kreinin, C. Becker. Validation of Energy Yield Model for Bifacial Solar Cells and Prediction of Perovskite/silicon Tandem Solar Cell Performance. (Poster presentation), TandemPV, Freiburg, 30 May - 1 June 2022.

  • J. Münchmeyer, J. Woollam, F. Tilmann, A. Rietbrock, D. Lange, ..., and H. Soto. SeisBench: A toolbox for machine learning in seismology. Helmholtz AI Conference, Dresden, Germany, 2-3 June 2022.

  • B. Ghosh, S. Garg, M. Motagh. Automatic flood detection from Sentinel-1 data using Deep learning architectures. (Oral presentation), ISPRS Congress, Nice, France, 6-11 June 2022. 

  • T. Rettelbach, M. Langer, I. Nitze, B. Jones, V. Helm, J-C. Freytag, and G. Grosse. From images to hydrologic networks - Understanding the Arctic landscape with graphs. (Oral presentation), 34th International Conference on Scientific and Statistical Database Management, Copenhagen, Denmark, 6-8 July 2022.

  • L. Nazaretyan, M. Kircher, and U. Leser. Benchmarking machine learning methods for identification of mislabeled data. (Poster presentation), ECCB 2022, Sitges, Spain, September 18-21, 2022.

  • T. Kirschbaum, B. von Seggern, J. Dzubiella, A. Bande and F. Noé. Machine Learning Frontier Orbital Energies of Nanodiamonds. (Poster presentation), 58th Symposium of Theoretical Chemistry, Heidelberg, Germany, 18-22 September 2022.

  • P. Graniero, G.A.F. Basulto, R. Schlatmann, R. Klenk, and C. Ulbrich. Online Implementation of a Multiple Linear Regression Model for CIGS Photovoltaic Module Performance. (Poster presentation), 8th World Conference on Photovoltaic Energy Conversion (WCPEC-8), Milan, Italy,  26-30 September 2022.

  • C. Utama, C. Meske, J. Schneider, and C. Ulbrich. Reactive power control in photovoltaic systems through (explainable) artificial intelligence. (Poster presentation), 8th World Conference on Photovoltaic Energy Conversion (WCPEC-8), Milan, Italy, 26-30 September 2022.

  • K. Styp-Rekowski, I. Michaelis, C. Stolle, and O. Kao. Physics-informed Neural Network for Platform Magnetometer Calibration. (Oral Presentation), Swarm Data Quality Workshop, Uppsala, Sweden, 10-14 October 2022.

  • C. Utama, B. Karg, C. Meske, and S. Lucia. Explainable artificial intelligence for deep learning-based model predictive controllers. (Oral presentation), 26th International Conference on System Theory, Control and Computing (ICSTCC), Online, 19-21 October 2022.

  • J. Bader, K. Styp-Rekowski, L. Döhler, S. Becker, and O. Kao. Macaw: The Machine Learning Magnetometer Calibration Workflow. (Oral Presentation), IEEE International Conference on Data Mining, Orlando, Florida, USA, 28 November – 1 December 2022.

2021

2021

  • E. Robertson, L. Jaruingue, L. Messner, L. Esguerra, G. Gallego, K. Lüdge, and J. Wolters. A scheme for optical reservoir computers with atomic memory. (Poster presentation), Hot Vapor Workshop, Stuttgart, Online, 22-24 March 2021.

  • F. van Geffen, B. Heim, U. Herzschuh, L. Pestryakova, E. Zakharov, R. Hänsch, B. Demir, B. Kleinschmit, M.Förster, and S. Kruse. SiDro forest: Siberian drone-mapped forest inventory. (Oral presentation), Arctic Science Summit Week, Portugal, Online,19-26 March 2021.

  • S. Redyuk, Z. Kaoudi, V. Markl, and S. Schelter. Automating data quality validation for dynamic data ingestion.  (Oral presentation), International Conference on Extending Database Technology (EDBT), Nicosia, Cyprus, 23-26 March 2021. https://www.youtube.com/watch?v=v9IR1zjqAek

  • G. Pfalz, B. Diekmann, J-C. Freytag, and B.K. Biskaborn. Harmonizing heterogeneous multi-proxy data from Arctic lake sediment records. (PICO presentation), EGU General Assembly, Online, 19–30 April 2021, EGU21-9401. https://doi.org/10.5194/egusphere-egu21-9401

  • F. van Geffen, B. Heim, U. Herzschuh, L. Pestryakova, E. Zakharov, R. Hänsch, B. Demir, B. Kleinschmit, M. Förster, and S. Kruse. SiDro Forest: Siberian drone-mapped forest inventory. (PICO presentation), EGU General Assembly, Online, 19-30 April 2021, EGU21-15106. https://doi.org/10.5194/egusphere-egu21-15106

  • N. Veigel, H. Kreibich, and A. Cominola. Mining flood insurance Big Data to reveal the determinants of humans' flood resilience. (PICO presentation), EGU General Assembly, Online, 19–30 Apr 2021. https://doi.org/10.5194/egusphere-egu21-3042

  • S. Agarwal, N. Tosi, P. Kessel, S. Padovan, D. Breuer, and G. Montavon. Towards constraining Mars' thermal evolution using machine learning. (PICO presentation), EGU General Assembly, Online, 19-30 Apr 2021. https://doi.org/10.5194/egusphere-egu21-4044

  • J. Münchmeyer, D. Bindi, U. Leser, and F. Tilmann. Insights into deep learning for earthquake magnitude and location estimation. (PICO presentation), EGU General Assembly, Online, 19-30 April 2021. https://doi.org/10.5194/egusphere-egu21-4718

  • B. Groenke, M. Langer, G. Gallego, and J. Boike. Learning soil freeze characteristic curves with universal differential equations, (PICO presentation), EGU General Assembly, Online, 19–30 Apr 2021. https://doi.org/10.5194/egusphere-egu21-13409

  • B. Ghosh, M. Motagh, M.H. Haghighi, and T. Walter. Using minimal spanning tree based ICA optimization for volcanic unrest determination. (Oral presentation), EGU General Assembly, Online, 19-30 April, 2021.

  • J. Münchmeyer, D. Bindi, U. Leser, and F. Tilmann. The Transformer earthquake alerting model: A data driven approach to early warning. (Oral presentation), Seismological Society of America (SSA) Annual Meeting, Online, 19-23 April 2021.

  • T. Gimm, X. Wang, K. Palczynski, A. Bande, and J. Dzubiella. Nanodiamond-adsorbate interactions studied by DFT. (Poster presentation), Bunsen-Tagung 2021 - Multi-scale modelling & and physical chemistry of colloids, Online, 10-12 May 2021.

  • M. Saenger, L. Weber and U. Leser. WBI at MEDIQA 2021: Summarizing consumer health questions with generative transformersBioNLP Workshop - MEDIQA, 11 June 2021. https://www.aclweb.org/anthology/2021.bionlp-1.9.pdf

  • P. Tillmann,  K. Jäger, E.A. Katz, and C. Becker. Relaxed current-matching constraints in perovskite/silicon tandem solar cell by bifacial operation and luminescent coupling. (Oral presentation), IEEE Photovoltaic Specialists Conference (PVSC), Online, 20-25 June 2021.

  • B. Ghosh, M.H. Haghighi, M. Motagh, and S. Maghsudi. Using generative adversarial networks for extraction of InSAR signals from large-scale Sentinel-1 interferograms by improving tropospheric noise correction,  (Oral presentation), ISPRS Congress, 4-10 July 2021.

  • P. Graniero, D. Rößler, C. Ulbrich, and N. Kliewer. Potentials and challenges for integration of electric bus fleets and PV-systems. (Oral presentation), 31st European Conference on Operational Research (EURO 2021), Athens, Greece / Online, 11-14 July 2021.

  • A.H.C. Vlot, S. Maghsudi, and U. Ohler. Single-cEll Marker IdentificaTiON by Enrichment Scoring. (Poster and oral presentation), ISMB/ECCB 2021, Online, 25-30 July 2021.

  • L. Nazaretyan. The Regulatory Mendelian Mutation (ReMM) score for GRCh38. (Poster presentation), ISMB/ECCB 2021, Online, 25-30 July, 2021.

  • H. Stolte. Checking plausibility in exploratory data analysis.  (Oral presentation), 47th International Conference on Very Large Databases, Copenhagen, Denmark, 16-20 August 2021. http://ceur-ws.org/Vol-2971/paper08.pdf

  • K. Styp-Rekowski, C. Stolle, O. Kao, and I. Michaelis. Satellite Platform Magnetometer Calibration Using Machine Learning. (Oral Presentation), Joint Scientific Assembly IAGA-IASPEI, Online, 21-27 August 2021.

  • K. Styp-Rekowski, C. Stolle, O. Kao, and I. Michaelis. Automatic Calibration of Satellite Platform Magnetometers with Neural Network-based Time Shift Approximation. (Oral Presentation), Joint Scientific Assembly IAGA-IASPEI, Online, 21-27 August 2021.

  • L. Nazaretyan, M. Schubach, and M. Kircher. The Regulatory Mendelian Mutation (ReMM) score for GRCh38. (Poster presentation), ESHG 2021, Online, August 28–31, 2021.

  • S. Agarwal, N. Tosi, P. Kessel, D. Breuer, and G. Montavon. Deep learning for surrogate modelling of 2D mantle convection. (Oral presentation), German-Swiss Geodynamics Workshop 2021, Bad Belzig, 29 Aug–1 Sep 2021.

  • J. Nordin, N. Miranda, V. Brinnel, and J. van Santen. The AMPEL System as an official VRO community broker: Current developments and applications. (Oral presentation), Virtual Annual Meeting of the German Astronomical Society, 13-17 September, 2021.

  • T. Gimm, X. Wang, K. Palczynski, A. Bande, and J. Dzubiella. Nanodiamond-adsorbate interactions studied by DFT. (Poster presentation), 57th Symposium of Theoretical Chemistry, Online, 20-24 September 2021.

  • J. Münchmeyer, J. Woollam, D. Jozinovic, J. Saul, A. Michelini, C. Giunchi, T. Diehl, F. Haslinger, D. Lange, A. Rietbrock, and F. Tilmann. SeisBench: A framework for machine learning in seismology. (Oral presentation) 37th General Assembly of the European Seismological Commission, Online, 19-24 September 2021.

  • S. Agarwal, N. Tosi, P. Kessel, D. Breuer, and G. Montavon. Deep learning for surrogate modelling of 2D mantle convection. (Oral presentation), European Planetary Science Congress 2021, Online, 13–24 Sep 2021. https://doi.org/10.5194/epsc2021-218

  • A.H.C. Vlot, S. Maghsudi, and U. Ohler. Identification of cis-regulatory regions using Single-cEll Marker IdentificaTiON by Enrichment Scoring (SEMITONES). (Poster presentation), EMBO Workshop Enhanceropathies: Understanding enhancer function to understand human disease, 6-9 October 2021.

  • P. Graniero. Data driven mitigation measures in advanced PV plant monitoring. (Oral presentation), Intersolar Conference, Munich, Germany, 6-7 October 2021.

  • K. Styp-Rekowski, C. Stolle, I. Michaelis, and O. Kao. Machine Learning-based Information Extraction from Non-dedicated Sensors. (Oral Presentation), Photonics Days Berlin Brandenburg, Berlin, Germany, 4-7 October 2021.

  • K. Styp-Rekowski, C. Stolle, I. Michaelis, and O. Kao. Calibration of GRACE-FO and GOCE Platform Magnetometers Using Machine Learning. (Oral Presentation), Swarm Data Quality Workshop, Athens, Greece, 11-16 October 2021.

  • T. Rettelbach, M. Langer, I. Nitze, B. Jones, V. Helm, J-C. Freytag, and G. Grosse. Quantifying erosional dynamics in ice-wedge networks with computer vision and graph theory. (Invited talk), Regional Conference on Permafrost, Online, 24-29 October 2021.

  • B. Groenke, M. Langer, G. Gallego and J. Boike. A model-driven approach to quantifying uncertainty in permafrost temperature trends. (Poster presentation), 6th Data Science Symposium, Bremen, Germany, 8-9 Nov 2021.

  • S. Agarwal, N. Tosi, P. Kessel, D. Breuer, and G. Montavon. Deep learning for surrogate modelling of 2D mantle convection. (Oral presentation), The 74th Annual Meeting of the Division of Fluid Dynamics, Online, 21-23 Nov 2021.

  • T. Rettelbach, M. Langer, I. Nitze, B. Jones, V. Helm, J-C. Freytag, and G. Grosse. Evaluating the effects of tundra fires on soil microtopography and hydrologic surface networks in polygonal permafrost landscapes. (Oral presentation), AGU Fall Meeting, New Orleans, USA / Online, 13-17 December 2021.

  • J. Münchmeyer, U. Leser, and F. Tilmann. A probabilistic view of earthquake rupture predictability. (Oral presentation), AGU Fall Meeting, New Orleans, USA / Online 13-17 December 2021.

  • N. Veigel, H. Kreibich, and A. Cominola. Mining Flood Insurance Big Data to incorporate behavioural and social aspects in flood risk modelling. (Poster presentation), AGU Fall Meeting, New Orleans, USA / Online, 13–17 Dec 2021.

  • S. Agarwal, N. Tosi, P. Kessel, D. Breuer, and G. Montavon. A machine learning framework for constraining mantle convection parameters. (Oral presentation), American Geophysical Union Fall Meeting,  New Orleans, USA, 13-17 Dec 2021.

  • K. Styp-Rekowski, C. Stolle, I. Michaelis, and O. Kao. Calibration of the GRACE-FO Satellite Platform Magnetometers and Co-Estimation of Intrinsic Time Shift in Data. (Oral Presentation), IEEE Big Data 2021, Online, 15-18 December 2021.

2020

2020

  • B. Ghosh, M. Motagh, S. Maghsudi, and M.H. Haghighi. Reduction of tropospheric noise delay from large-scale interferograms using generative adversarial networks. (Oral presentation), 40th Annual Scientific and Technical Conference of the DGPF, Stuttgart, Germany, 4 - 6 March 2020.

  • S. Redyuk, V. Markl, and S. Schelter. Towards unsupervised data quality validation on dynamic data.  (Workshop paper and presentation), ETMLP 2020, Copenhagen, Denmark, 30 March 2020. https://www.youtube.com/watch?v=Xhq8X64RA1Q

  • S. Agarwal, N. Tosi, P. Kessel, D. Breuer, S. Padovan, and G. Montavon. Mars’ thermal evolution from machine-learning-based 1D surrogate modelling, (Oral presentation), EGU General Assembly, Online, 4-8 May 2020.

  • J. Münchmeyer, D. Bindi, U. Leser, and F. Tilmann. End-to-end PGA estimation for earthquake early warning using transformer networks. (Oral presentation), EGU General Assembly, Online, 4-8 May 2020.

  • B. Ghosh, M. Motagh, S. Maghsudi, and M.H. Haghighi. Automatic flood monitoring based on SAR intensity and interferometric coherence using machine learning. (Oral presentation), EGU General Assembly, Online, 4-8 May, 2020.

  • H. Lilienkamp, F. Cotton, G. Caire, G. Weatherill, and S. von Specht. Fully data-driven, partially non-ergodic ground motion modeling using convolutional neural networks. (Poster presentation), Taiwan Earthquake Research Center Annual Meeting, 20-22 October 2020.

  • P. Tillmann, C. Becker, and K. Jäger. Analysing the angular reflection losses of bifacial solar cells.  (Poster presentation), European Photovoltaic Solar Energy Conference and Exhibition (EU PVSEC), Online, 7-11 September 2020.

  • A.H.C. Vlot, S. Maghsudi, and U. Ohler. Identification of marker genes and cis-regulatory regions using Single-cEll Marker IdentificaTiON by Enrichment Scoring (SEMITONES). (Poster presentation), 13th annual RECOMB/ISCB Conference on Regulatory & Systems Genomics with DREAM Challenges, 16-19 September 2020.

  • P. Graniero, A. Louwen, R. Schlatmann, and C. Ulbrich. Comparison of different data sources for  Machine Learning algorithms in photovoltaic output power estimation. (Poster presentation), 37th EU PVSEC, Online, 7-11 September 2020.

  • S. Agarwal, N. Tosi, P. Kessel, D. Breuer, S. Padovan, and G. Montavon. Learning high dimensional surrogates from mantle convection simulations. (Oral presentation), 73rd Annual Meeting of the APS Division of Fluid Dynamics, Online, 23 November 2020.

  • J. Münchmeyer, D. Bindi, U. Leser, and F. Tilmann. The transformer earthquake alerting model: Improving earthquake early warning with deep learning. (Oral presentation), AGU Fall Meeting, Online, 1-17 December 2020.

  • T. Rettelbach, M. Langer, I. Nitze, B. Jones. J. Boike, J-C. Freytag, and G. Grosse. Potential von Graphen für die quantitative Analyse von tauenden Eiskeilpolygonnetzwerken. (Oral presentation), 11. Treffen des AK Permafrost der DGP, Online, 11 December 2020.

  • T. Rettelbach, G. Grosse, I. Nitze, J. Brauchle, T. Bucher, M. Gessner, B.M. Jones, J. Boike, M. Langer, and J-C. Freytag. A quantitative graph-based assessment of ice-wedge trough dynamics in polygonal thermokarst landscapes of the Anaktuvuk River fire scar. (Oral presentationh), AGU Fall Meeting, Online, 1-17 December 2020.

2019

2019

  • J. Münchmeyer, D. Bindi, C. Sippl, and F. Tilmann. Increasing magnitude scale consistency by combining multiple waveform features through Machine Learning. (Oral presentation), EGU General Assembly, Vienna, 7-12 April 2019.

  • S. Redyuk. Automated documentation of end-to-end experiments in data science. (Workshop paper and presentation), ICDE’19, Macau, China, 8-11 April, 2019. 10.1109/ICDE.2019.00243

  • H. Lilienkamp, G. Weatherill, F. Cotton, and G. Caire. The role of spatial cross-correlation structures of ground motion fields forseismic risk assessment of spatially distributed assets and infrastructurenetworks.  (Poster presentation), EGU General Assembly, Vienna, Austria, 7–12 April 2019.

  • S. Redyuk, S. Schelter, T. Rukat, V. Markl, and F. Biessmann. Learning to validate the predictions of black box machine learning models on unseen data. (Workshop paper and presentation), HILDA’19, Amsterdam, Netherlands, 5 July, 2019. doi.org/10.1145/3328519.3329126

  • S. Agarwal, N. Tosi, D. Breuer, S. Padovan, P. Kessel, and G. Montavon. Unravelling interior evolution of terrestrial planets using machine learning. (Oral presentation), Artificial Intelligence in Astronomy at ESO, Garching, Germany, 22-26 July 2019.

  • L. Weber, P. Minervini, J. Münchmeyer, U. Leser, and T. Rocktäschel. NLProlog: Reasoning with weak unification for question answering in natural language.  (Poster presentation), 57th Annual Meeting of the Association for Computational Linguistics, Florence, Italy, 28 July - 2 August, 2019.

  • G. Pfalz, B. Diekmann, J-C. Freytag, and B.K. Biskaborn. Decipher Arctic lakes ecosystem dynamics. (Poster presentation), YES Congress 2019, Berlin, Germany, 9-13 September, 2019.

  • S. Agarwal, N. Tosi, D. Breuer, P. Kessel, and G. Montavon. Using machine learning to predict 1D steady-state temperature profiles from compressible mantle convection simulations. (Oral presentation), 72nd Annual Meeting of the APS Division of Fluid Dynamics, Seattle, USA, 23-26 November 2019.

  • J. Münchmeyer, D. Bindi, U. Leser, and F. Tilmann. Convolutional event embeddings for fast probabilistic earthquake assessment. (Poster presentation), AGU General Assembly, San Francisco, 9-13 December 2019.

  • H. Lilienkamp, S. Specht, G. Weatherill, and F. Cotton. Exploring the physics and uncertainties in spatial cross-correlation models for ground motion intensity measures.  (Oral presentation), AGU General Assembly, San Francisco, USA, 9–13 December 2019.