Christian Toth received his Dipl. Ing. degree in Information and Computer Engineering from Graz University of Technology in 2020. He is currently pursuing a Ph.D. under the supervision of Franz Pernkopf and Robert Peharz. His research interests include causal inference, structure learning, Bayesian methods and probabilistic modeling.

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Courses

• Fundamentals of discrete-time signals and systems
• Digital Signal Processing and Communications Laboratory
• Nonlinear Signal Processing

Student Projects

• Synthesizing Infomap - A Kullback-Leibler Divergence-Based Approach To Community Detection

PhD Thesis

• Bayesian Causal Inference in the Presence of Structural Uncertainty

Publications

• Conference paper Toth C., Knoll C., Pernkopf F. & Peharz R. (2025) Effective Bayesian Causal Inference via Structural Marginalisation and Autoregressive Orders. in 28th International Conference on Artificial Intelligence and Statistics, AISTATS 2025. [more info]
• Conference paper Toth C., Knoll C., Pernkopf F. & Peharz R. (2024) Effective Bayesian Causal Inference via Structural Marginalisation and Autoregressive Orders. in 2nd SPIGM - ICML 2024 Workshop on Structured Probabilistic Inference & Generative Modeling. [more info]
• Conference paper Toth C., Lorch L., Knoll C., Krause A., Pernkopf F., Peharz R. & Kügelgen J. (2023) Active Bayesian Causal Inference. in 36th Conference on Neural Information Processing Systems. [more info]
• Journal article Toth C., Helic D. & Geiger B. (2022) Synwalk: community detection via random walk modelling. in Data Mining and Knowledge Discovery, 36(2), p. 739-780. [more info] [doi]