Maxim Majlatow

According to our database, Maxim Majlatow authored at least 8 papers between 2023 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

From Theory to Practice: Real-World Use Cases on Trustworthy LLM-Driven Process Modeling, Prediction and Automation.

Peter Pfeiffer, Alexander Rombach, Maxim Majlatow, Nijat Mehdiyev

CoRR, June, 2025

Quantifying and explaining machine learning uncertainty in predictive process monitoring: an operations research perspective.

Nijat Mehdiyev, Maxim Majlatow, Peter Fettke

Ann. Oper. Res., April, 2025

Integrating permutation feature importance with conformal prediction for robust Explainable Artificial Intelligence in predictive process monitoring.

Nijat Mehdiyev, Maxim Majlatow, Peter Fettke

Eng. Appl. Artif. Intell., 2025

Augmenting post-hoc explanations for predictive process monitoring with uncertainty quantification via conformalized Monte Carlo dropout.

Nijat Mehdiyev, Maxim Majlatow, Peter Fettke

Data Knowl. Eng., 2025

2024

Counterfactual Explanations in the Big Picture: An Approach for Process Prediction-Driven Job-Shop Scheduling Optimization.

Nijat Mehdiyev, Maxim Majlatow, Peter Fettke

Cogn. Comput., September, 2024

Communicating Uncertainty in Machine Learning Explanations: A Visualization Analytics Approach for Predictive Process Monitoring.

Nijat Mehdiyev, Maxim Majlatow, Peter Fettke

Proceedings of the Explainable Artificial Intelligence, 2024

2023

Interpretable and Explainable Machine Learning Methods for Predictive Process Monitoring: A Systematic Literature Review.

Nijat Mehdiyev, Maxim Majlatow, Peter Fettke

CoRR, 2023

Explainable Artificial Intelligence Meets Uncertainty Quantification for Predictive Process Monitoring.

Nijat Mehdiyev, Maxim Majlatow, Peter Fettke

Proceedings of the 2nd International Workshop on Process Management in the AI Era (PMAI 2023) co-located with 31st International Joint Conference on Artificial Intelligence (IJCAI 2023), 2023