Maxim Majlatow

11 papers Journal 9Unranked 2
YearRankTypeTitle / Venue / Authors
2025 J jnl
Augmenting post-hoc explanations for predictive process monitoring with uncertainty quantification via conformalized Monte Carlo dropout.
Data Knowl. Eng.
Nijat Mehdiyev, Maxim Majlatow, Peter Fettke
2025 J jnl
From Theory to Practice: Real-World Use Cases on Trustworthy LLM-Driven Process Modeling, Prediction and Automation.
CoRR
Peter Pfeiffer, Alexander Rombach, Maxim Majlatow, Nijat Mehdiyev
2025 J jnl
Integrating permutation feature importance with conformal prediction for robust Explainable Artificial Intelligence in predictive process monitoring.
Eng. Appl. Artif. Intell.
Nijat Mehdiyev, Maxim Majlatow, Peter Fettke
2025 J jnl
Interpretable and explainable machine learning methods for predictive process monitoring: a systematic literature review.
Artif. Intell. Rev.
Nijat Mehdiyev, Maxim Majlatow, Peter Fettke
2025 J jnl
Quantifying and explaining machine learning uncertainty in predictive process monitoring: an operations research perspective.
Ann. Oper. Res.
Nijat Mehdiyev, Maxim Majlatow, Peter Fettke
2024 — conf
Communicating Uncertainty in Machine Learning Explanations: A Visualization Analytics Approach for Predictive Process Monitoring.
xAI (3)
Nijat Mehdiyev, Maxim Majlatow, Peter Fettke
2024 J jnl
Counterfactual Explanations in the Big Picture: An Approach for Process Prediction-Driven Job-Shop Scheduling Optimization.
Cogn. Comput.
Nijat Mehdiyev, Maxim Majlatow, Peter Fettke
2023 J jnl
Communicating Uncertainty in Machine Learning Explanations: A Visualization Analytics Approach for Predictive Process Monitoring.
CoRR
Nijat Mehdiyev, Maxim Majlatow, Peter Fettke
2023 — conf
Explainable Artificial Intelligence Meets Uncertainty Quantification for Predictive Process Monitoring.
PMAI@IJCAI
Nijat Mehdiyev, Maxim Majlatow, Peter Fettke
2023 J jnl
Interpretable and Explainable Machine Learning Methods for Predictive Process Monitoring: A Systematic Literature Review.
CoRR
Nijat Mehdiyev, Maxim Majlatow, Peter Fettke
2023 J jnl
Quantifying and Explaining Machine Learning Uncertainty in Predictive Process Monitoring: An Operations Research Perspective.
CoRR
Nijat Mehdiyev, Maxim Majlatow, Peter Fettke