Gerrit Großmann
Postdoctoral Researcher
DFKI – Neuro-Mechanistic Modeling
Modeling and Simulation Group, Saarland University
Universität des Saarlandes
Campus D3 2 (DFKI), Room 2.24
66123 Saarbrücken
Germany
About Me
Note: This profile is no longer maintained. Please visit my updated personal academic website at gerritgrossmann.de.
Research
I am working on numerical methods (like fast simulations or model reduction techniques) for the analysis of stochastic dynamical processes unfolding on complex networks. My research aims at understanding how stochastic interactions, that are constrained by a network topology, shape collective emerging phenomena such as epidemics, rumors, blackouts in power grids, or burst in biological neural networks. The image shows a continuous-time SIS contagion process (infected nodes in red, healthy nodes in blue) on a geometric network.
Tutorials
- Spreading Dynamics in Complex Networks at the 20th Conference on Measurement, Modelling and Evaluation of Computing Systems (MMB), 2020 - Cancelled due to COVID-19 :(.
- I contributed to the deep learning for computer-aided drug design tutorial (T033 - T038) series.
Tools
- LumPy
- NetworkEpidemicPlayground (browser-based)
- More tools on Github.
Opinion Pieces
- 7 Reasons Not to Use ODEs for Epidemic Modeling
- Der Nutzen von Corona-Modellen bleibt ungeklärt (The usefulness of corona models remains uncertain), Saarbrücker Zeitung; Feb., 4th, 2022
Publications
- G. Großmann: (Poster abstract) Discriminator-Driven Diffusion Mechanisms for Molecular Graph Generation, ML4Molecules ELLIS workshop, 2023.
- G. Großmann: (Poster abstract) Deep Sets Are Viable Graph Learners, Complex Networks Conference, 2023.
- G. Großmann: (Poster abstract) Network Reconstruction via Sensitivity Analysis, Complex Networks Conference, 2023.
- M. Backenköhler et al.: (preprint) TeachOpenCADD goes Deep Learning: Open-source Teaching Platform Exploring Molecular DL Applications, 2023.
- G. Großmann, J. Zimmerlin, M. Backenköhler, V. Wolf: Unsupervised Relational Inference Using Masked Reconstruction, 2023.
- M. Backenköhler, L. Bortolussi, G. Großmann, V. Wolf: Abstraction-Guided Truncations for Stationary Distributions of Markov Population Models, 2021
- G. Großmann, M. Backenköhler, V. Wolf: Heterogeneity matters: Contact structure and individual variation shape epidemic dynamics, PLOS ONE, 2021, Preprint PDF.
- G. Großmann, M. Backenköhler, V. Wolf: Epidemic Overdispersion Strengthens the Effectiveness of Mobility Restrictions, MedRxiv, Poster Abstract, 2021.
- G. Großmann, L. Bortolussi, V. Wolf: Efficient Simulation of non-Markovian Dynamics on Complex Networks, PLOS one, PDF
- M. Backenköhler, L. Bortolussi, G. Großmann, V. Wolf: (TACAS 2021) Analysis of Markov Jump Processes under Terminal Constraints
- G. Großmann, M. Backenköhler, J. Klesen, V. Wolf: Learning Vaccine Allocation from Simulations, The 9th International Conference on Complex Networks and their Applications, 2020. Preprint PDF
- G. Großmann, M. Backenköhler, V. Wolf: Importance of Interaction Structure and Stochasticity for Epidemic Spreading: A COVID-19 Case Study, QEST 2020.
- G. Großmann, M. Backenköhler: (Poster Abstract) Birth-Death Processes Reproduce the Infection Footprint of Complex Networks, HSB 2020.
- G. Großmann, L. Bortolussi, V. Wolf: Rejection-Based Simulation of Non-Markovian Agents on Complex Networks, The 8th International Conference on Complex Networks and their Applications, 2019.
- G. Großmann, L. Bortolussi: Reducing Spreading Processes on Networks to Markov Population Models, QEST 2019, PDF.
- G. Großmann, V. Wolf: Rejection-Based Simulation of Stochastic Spreading Processes on Complex Networks HSB 2019, PDF.
- C. Kyriakopoulos, G. Großmann, V. Wolf, L. Bortolussi: Lumping of Degree-Based Mean Field and Pair Approximation Equations for Multi-State Contact Processes, Physical Review E, 2018.
- G. Großmann, C Kyriakopoulos, L Bortolussi, V Wolf: Lumping the Approximate Master Equation for Multistate Processes on Complex Networks, QEST 2018, PDF.
Education
Master
Saarland University
Lumping the Approximate Master Equation for Stochastic Processes on Complex Networks
Bachelor
Saarland University
Efficient Computation of Likelihoods in Large Markov Models
Publications (15)
2026
Chaotic and complex dynamics expose the limits of counterfactual reasoning
2026 — Scientific Reports (Sci Rep)
2024
Enhancing GNNs with Architecture-Agnostic Graph Transformations: A Systematic Analysis
2024 — Hocine Cherifi; Murat Donduran; Luis M. Rocha; Chantal Cherifi; Onur Varol;: International Conference on Complex Networks and Their Applications
2023
Unsupervised relational inference using masked reconstruction
2023 — Applied Network Science
2021
Epidemic overdispersion strengthens the effectiveness of mobility restrictions
2021 — HSCC ‘21: Proceedings of the 24th International Conference on Hybrid Systems: Computation and Control. ACM International Conference on Hybrid Systems: Computation and Control (HSCC-2021), May 19-21, Nashville,, Tennesse, USA
Analysis of Markov jump processes under terminal constraints
2021 — Tools and Algorithms for the Construction and Analysis of Systems. International Conference on Tools and Algorithms for the Construction and Analysis of Systems (TACAS-2021), 27th International Conference, TACAS 2021, Held as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2021, March 27 - April 1, Luxembourg City, Luxembourg
Abstraction-Guided Truncations for Stationary Distributions of Markov Population Models
2021 — Quantitative Evaluation of Systems
2020
Learning Vaccine Allocation from Simulations
2020 — Complex Networks & Their Applications IX. International Conference on Complex Networks and their Applications (COMPLEX NETWORKS-2020), Proceedings of the Ninth International Conference on Complex Networks and Their Applications, December 1-3, Madrid, Spain
Importance of Interaction Structure and Stochasticity for Epidemic Spreading: A COVID-19 Case Study
2020 — Quantitative Evaluation of Systems. International Conference on Quantitative Evaluation of Systems (QEST-2020), 17th International Conference, QEST 2020, October 31 - September 1, Vienna, Austria
Rejection-Based Simulation of Non-Markovian Agents on Complex Networks
2020 — Complex Networks and Their Applications VIII
2019
Rejection-Based Simulation of Stochastic Spreading Processes on Complex
2019 — Hybrid Systems Biology - 6th International Workshop, Revised Selected Papers. International Workshop on Hybrid Systems Biology (HSB-2019), April 6-7, Prague, Czech Republic
Reducing Spreading Processes on Networks to Markov Population Models
2019 — Quantitative Evaluation of Systems
2018
Lumping the Approximate Master Equation for Multistate Processes on Complex Networks
2018 — Quantitative Evaluation of Systems
Teaching (13)
Bridging the Gap: Language Models and Structured Knowledge in AI
, in Summer 2024
Saarland UniversityAdvanced Topics in Diffusion Modeling: From Theory to Implementation
, in Winter 2023/24
Saarland UniversityAI for the Social Good
, in Summer 2023
Saarland UniversityDeep Generative Diffusion Models
, in Winter 2022/23
Saarland UniversityDeep Learning for Drug Discovery
, in Summer 2022
Saarland UniversityConcurrent Programming
, in Summer 2021
Saarland UniversityExploring Graph Neural Networks
, in Summer 2021
Saarland UniversityStatistics Lab
, in Summer 2020
Saarland UniversityExploring Complex Network Dynamics
, in Winter 2019/20
Saarland UniversityProbabilistic Models and Data Analysis
, in Summer 2019
Saarland UniversityRingvorlesung: Perspektiven der Informatik
, in Winter 2018/19
Saarland UniversityProbabilistic Models of Concurrency
, in Winter 2018/19
Saarland UniversityPattern and Speech Recognition
Saarland University
Supervised Students (8)
Nesara Belakere Lingarajaiah
Small Molecule Generation and Optimization: A GNN-VAE Appraoch
Master's Thesis, 2024
Magnus Cunow
Computer-Aided Molecular Generation Using Optimal Transport and Variational Autoencoders
Bachelor's Thesis, 2024
Joshgun Guliyev
Network Reconstruction Using Deep Learning and Sensitivity Analysis
Master's Thesis, 2023
Janine Lohse
Learning the Function of Neural Networks in Deep Weight Spaces
Research Immersion Lab, 2023
Yan Yan Lau
Adapting the Approximate Master Equations for Realistic Epidemic and Network Dynamics
Bachelor's Thesis, 2022
Julian Zimmerlin
Learning Dynamical Processes to Infer the Underlying Network Structure
Bachelor's Thesis, 2021
Jonas Klesen
Learning vaccine allocation strategies to control epidemic outbreaks on networks
Research Immersion Lab, 2020
Lisa Heidmann
Effects of Interventions on the COVID-19 Outbreak: A Network-based Approach
Bachelor's Thesis, 2020