S.W.Mogensen, Weak equivalence of local independence graphs, arXiv
S.W.Mogensen, O.O.Aalen, S.Strohmaier, Time-dependent mediators in survival analysis: Graphical representation of causal assumptions, arXiv
G.Manten, C.Casolo, E.Ferrucci, S.W.Mogensen, C.Salvi, N.Kilbertus, Signature Kernel Conditional Independence Tests in Causal Discovery for Stochastic Processes, arXiv
Peer reviewed
A.Rieckmann, S.Nielsen, P.Dworzynski, H.Amini, S.W.Mogensen, I.B.Silva, A.Y.Chang, O.A.Arah, W.Samek, N.H.Rod, C.T.Ekstrøm, C.S.Benn, P.Aaby, A.B.Fisker, Discovering Subgroups of Children With High Mortality in Urban Guinea-Bissau: Exploratory and Validation Cohort Study, JMIR Public Health and Surveillance 10:e48060, 2024, link
S.W.Mogensen, Faithful graphical representations of local independence, to appear in Proceedings of the 27th International Conference on Artificial Intelligence and Statistics (AISTATS), 2024, arXiv
S.W.Mogensen, K.Rathsman, P.Nilsson, Causal discovery in a complex industrial system: A time series benchmark, in Proceedings of the 3rd Conference on Causal Learning and Reasoning (CLeaR), 2024, arXiv, data, code, and how to get started
A.Bregoli, K.Rathsman, M.Scutari, F.Stella, S.W.Mogensen, Analyzing complex systems with cascades using
continuous-time Bayesian networks, in Proceedings of the 30th International Symposium on Temporal Representation and Reasoning (TIME), 2023, link
S.W.Mogensen, Instrumental Processes Using Integrated
Covariances, in Proceedings of the 2nd Conference on Causal Learning and Reasoning (CLeaR), 2023, pdf
S.Weichwald, S.W.Mogensen, T.E.Lee, D.Baumann, O.Kroemer, I.Guyon, S.Trimpe, J.Peters, N.Pfister, Learning by Doing: Controlling a Dynamical System using Causality, Control, and Reinforcement Learning, in Proceedings of the NeurIPS 2021 Competitions and Demonstrations Track, PMLR 176, 2022, link
S.W.Mogensen, N.R.Hansen, Graphical modeling of stochastic processes driven by correlated noise, Bernoulli 28(4): 3023-3050, 2022, link, arXiv, blog post
S.W.Mogensen, Equality Constraints in Linear Hawkes Processes, in Proceedings of the 1st Conference on Causal Learning and Reasoning (CLeaR), 2022, pdf
A.Lund, S.W.Mogensen, N.R.Hansen, Soft Maximin Estimation for Heterogeneous Data, Scandinavian Journal of Statistics, 2022, link
C. Øland, S.W.Mogensen, A.Rodrigues, C.S.Benn, P.Aaby, Reduced Mortality After Oral Polio Vaccination and Increased Mortality After Diphtheria-Tetanus-Pertussis Vaccination in Children in a Low-Income Setting, Clinical Therapeutics 43(1): 172-184, 2021, link
S.W.Mogensen, N.R.Hansen, Markov equivalence of marginalized local independence graphs, Annals of Statistics 48(1), 2020, link, arXiv
S.W.Mogensen, Causal screening in dynamical systems, in Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence, 2020, pdf, supp
S.W.Mogensen, D.Malinsky, N.R.Hansen, Causal learning for partially observed stochastic dynamical systems, in Proceedings of the 34th Conference on Uncertainty in Artificial Intelligence, 2018, pdf, supp, talk
P.Aaby, S.W.Mogensen, A.Rodrigues, C.S.Benn, Evidence of increase in mortality after the introduction of diphtheria-tetanus-pertussis vaccine to children aged 6-35 months in Guinea-Bissau: A time for reflection?, Frontiers in Public Health 6, 2018, pdf
C.B.Patsche, F.Rudolf, S.W.Mogensen, A.Sifna, V.F.Gomes, S.Byberg, C.Wejse, Low prevalence of malnourishment among household contacts of patients with tuberculosis in Guinea-Bissau, The International Journal of Tuberculosis and Lung Disease, 21(6), 2017, link
S.W.Mogensen1, A.Andersen1, A.Rodrigues, C.S.Benn, P.Aaby, The introduction of diphtheria-tetanus-pertussis and oral polio vaccine among young infants in an urban African community: A natural experiment, EBioMedicine 17: 192-8, 2017, 1: equal contribution, pdf
S.W.Mogensen, A.H.Petersen, A.Buchardt, N.R.Hansen, Survival prognosis and variable selection: A case study for metastatic castrate resistant prostate cancer patients, F1000Research, 5(2680), 2016, pdf
S.W.Mogensen, P.Aaby, L.Smedman, C.L.Martins, A.Rodrigues, C.S.Benn, H.Ravn, Introduction of standard measles vaccination in an urban African community in 1979 and overall child survival: A reanalysis of data from a cohort study, BMJ Open, 6(12):e011317, pdf, 2016
Talks
Estimation of causal effects using covariate adjustment in vector autoregressive processes, EuroCIM, Copenhagen, April 2024
Graphical models of local independence in stochastic processes, Seminar on
Statistics and Data Science, Technical University of Munich, February 2024 (invited)
Graphical models of local independence in stochastic processes, Statistics Seminar, EPFL, Lausanne, October 2023 (invited)
Learning causal graphs of multivariate stochastic processes from tests of local independence or Granger causality, Causal inference for time series data (workshop @ UAI 2023), Pittsburgh, August 2023, slides(invited)
Learning Granger-causal graphs from partially observed multivariate time series, Nordstat, Gothenburg, June 2023
Instrumental processes using integrated covariances, EuroCIM, Oslo, April 2023
Learning Granger-causal graphs from partially observed multivariate time series, Data Science and AI seminar, Department of Computer Science and Engineering,
Chalmers and University of Gothenburg, March 2023 (invited)
Instrumental processes using integrated covariances: An example of causal inference in engineering, Danish Data Science 2022, Billund, November 2022 (invited)
Instrumental processes using integrated covariances, Department of Statistics, School of Economics and Management, Lund University, October 2022 (invited)
Conditional instrumental variables in linear state-space models, Swedish Control Conference, Luleå, June 2022
Graphical structure learning and local independence in stochastic processes, Department of Informatics, Systems and Communication, University of Milano-Bicocca, April 2022 (invited)
Graphical structure learning in multivariate stochastic processes, DESY, Intelligent Process Control Seminar, virtual, January 2022 (invited)
Equality Constraints in Linear Hawkes Processes, Causal Inference Workshop at UAI, virtual, July 2021, talk, extended abstract, slides, poster
Estimation in Hawkes processes as a missing data problem, EcoSta2021, virtual, June 2021 (invited)
Causal screening for dynamical systems, UAI-20, virtual, August 2020
Causal models of Hawkes processes, Causal inference working group, Department of Biostatistics, Johns Hopkins University, December, 2019 (invited)
Graphical modeling of local independence in dynamical systems, Department of Statistics, University of Washington, November 2019 (invited)
Causal models of Hawkes processes, Causal inference working group,
Department of Statistics, University of Seattle, October, 2019
Causal learning for linear SDEs, EuroCIM, Bremen, March 2019
Graphical modeling of Ornstein-Uhlenbeck processes, ASC2019, Tokyo, February 2019 (invited)
Marginalized local independence graphs, CMStatistics, Pisa, December 2018 (invited)
Causal learning of partially observed stochastic dynamical systems, UAI-18, Monterey, August 2018, talk
Structure learning and linear stochastic differential equations, Nordstat, Tartu, June 2018 (invited)
Markov equivalence in graphical models for partially observed stochastic processes, ACIC, Pittsburgh, May 2018
Markov equivalence in graphical models for partially observed stochastic processes, Symposium on Statistics in Complex Systems, Copenhagen, April 2018 (invited)
Other
Kausal inferens: En historie om faldgruber ved prædiktion (in Danish) talk at Danish ASTIN (a chapter of Den Danske Aktuarforening) giving an introduction to causal inference, November 2022
UAI 2022 Tutorial, Graphical Models Meet Temporal Point Processes (with Debarun Bhattacharjya, Abir De, and Tian Gao), slides
PhD thesis, Graphical modeling in dynamical systems, pdf
Poster presentation: Sparse maximin aggregation of neuronal activity, SPARS, Lisbon, June 2017, extended abstract
