I am an associate professor in machine learning.

My main research interests lie within probabilistic graphical models, especially in structure learning in Bayesian networks. 

List of my publications can be found in my google scholar profile.

Academic article

• Miraki, Amir; Parviainen, Pekka; Arghandeh, Reza (2024). Electricity demand forecasting at distribution and household levels using explainable causal graph neural network. (external link)
• Kim, Hyeongji; Choi, Changkyu; Kampffmeyer, Michael Christian et al. (2024). ProxyDR: Deep Hyperspherical Metric Learning with Distance Ratio-Based Formulation. (external link)
• Fiedler, Johannes; Palau, Adria Salvador; Osestad, Eivind Kristen et al. (2023). Realistic mask generation for matter-wave lithography via machine learning. (external link)
• Kim, Hyeongji; Parviainen, Pekka; Malde, Ketil (2023). Measuring Adversarial Robustness using a Voronoi-Epsilon Adversary. (external link)
• Gillot, Pierre; Parviainen, Pekka (2022). Convergence of Feedback Arc Set-Based Heuristics for Linear Structural Equation Models. (external link)
• Håvardstun, Brigt Arve Toppe; Ferri, Cesar; Hernández-Orallo, José et al. (2022). On the trade-off between fidelity and teaching complexity. (external link)
• Gillot, Pierre; Parviainen, Pekka (2020). Scalable Bayesian Network Structure Learning via Maximum Acyclic Subgraph. (external link)
• Talvitie, Topi; Parviainen, Pekka (2020). Learning Bayesian Networks with Cops and Robbers. (external link)
• Qin, Xiangju; Blomstedt, Paul; Leppäaho, Eemeli et al. (2019). Distributed Bayesian matrix factorization with limited communication. (external link)

Academic lecture

• Malde, Ketil; Parviainen, Pekka; Kim, Hyeongji (2023). Measuring Adversarial Robustness using a Voronoi-Epsilon Adversary. (external link)

Doctoral dissertation

• Kim, Hyeongji; Malde, Ketil; Parviainen, Pekka (2023). On the Significance of Distance in Machine Learning. (external link)

Academic chapter/article/Conference paper

• Håvardstun, Brigt Arve Toppe; Ferri, Cesar; Hernández-Orallo, José et al. (2023). XAI with Machine Teaching When Humans Are (Not) Informed About the Irrelevant Features. (external link)
• Gillot, Pierre; Parviainen, Pekka (2022). Learning Large DAGs by Combining Continuous Optimization and Feedback Arc Set Heuristics. (external link)

See a complete overview of publications in Cristin.