1 citations · 1 across the 13 of their papers we have counts for
14 papers
On the Potential of Multi-Task Learning in Predictive Process Monitoring
Lukas Kirchdorfer, Keyvan Amiri Elyasi, Heiner Stuckenschmidt
Predictive Process Monitoring (PPM) forecasts how ongoing organizational processes unfold, enabling information systems to move beyond execution support toward proactive analysis a…
Mind the Long Tail: Understanding the Difficulty of Delay Detection in Business Processes
Keyvan Amiri Elyasi, Lukas Kirchdorfer, Heiner Stuckenschmidt
The early detection of delayed cases in business processes is a critical capability for organizations. Predictive process monitoring (PPM) supports this task by using historical ev…
Revisiting Predictive Process Monitoring in the Age of Foundation Models: A Comparative Study of Sequence, Tabular, and LLM Approaches
Lennart Fertig, Lukas Kirchdorfer, Tobias Sesterhenn
Predictive process monitoring (PPM) leverages event logs to forecast the future of running process instances, for instance, predicting the next activity, the remaining time until c…
Temporal Knowledge Graph Forecasting under Distribution Shifts: A Synthetic Evaluation
Konrad Özdemir, Julia Gastinger, Lukas Kirchdorfer +1
Temporal knowledge graphs (TKGs) represent evolving relational systems, whose underlying data-generating processes often change over time. Yet, TKG forecasting models are commonly…
Organizational Memory for Agentic Business Process Execution
Lukas Kirchdorfer, Adrian Rebmann, Christian Warmuth +3
LLM-based agents offer new opportunities for automating business process execution beyond the limits of rule-based systems. However, general-purpose LLMs lack the organization-spec…
From Global Policies to Local Strategies: Multi-Objective Optimization of Resource-Specific Handover Policies
Lukas Kirchdorfer, Artemis Doumeni, Han van der Aa +1
Efficient resource allocation is a key challenge in business process management, with direct implications for cost, throughput time, and utilization. While recent Reinforcement Lea…
Formal Foundations of Agentic Business Process Management
Giuseppe De Giacomo, Timotheus Kampik, Lukas Kirchdorfer +2
Just like traditional BPM systems, agentic BPM systems are built around a specification of the process under consideration. Their distinguishing feature, however, is that the execu…
On the Simplification of Neural Network Architectures for Predictive Process Monitoring
Amaan Ansari, Lukas Kirchdorfer, Raheleh Hadian
Predictive Process Monitoring (PPM) aims to forecast the future behavior of ongoing process instances using historical event data, enabling proactive decision-making. While recent…
A Divide-and-Conquer Approach for Modeling Arrival Times in Business Process Simulation
Lukas Kirchdorfer, Konrad Özdemir, Stjepan Kusenic +2
Business Process Simulation (BPS) is a critical tool for analyzing and improving organizational processes by estimating the impact of process changes. A key component of BPS is the…
Rethinking BPS: A Utility-Based Evaluation Framework
Konrad Özdemir, Lukas Kirchdorfer, Keyvan Amiri Elyasi +2
Business process simulation (BPS) is a key tool for analyzing and optimizing organizational workflows, supporting decision-making by estimating the impact of process changes. The r…
AgentSimulator: An Agent-based Approach for Data-driven Business Process Simulation
Lukas Kirchdorfer, Robert Blümel, Timotheus Kampik +2
Business process simulation (BPS) is a versatile technique for estimating process performance across various scenarios. Traditionally, BPS approaches employ a control-flow-first pe…
Analytical Uncertainty-Based Loss Weighting in Multi-Task Learning
Lukas Kirchdorfer, Cathrin Elich, Simon Kutsche +3
With the rise of neural networks in various domains, multi-task learning (MTL) gained significant relevance. A key challenge in MTL is balancing individual task losses during neura…
Enabling Mixed Effects Neural Networks for Diverse, Clustered Data Using Monte Carlo Methods
Andrej Tschalzev, Paul Nitschke, Lukas Kirchdorfer +3
Neural networks often assume independence among input data samples, disregarding correlations arising from inherent clustering patterns in real-world datasets (e.g., due to differe…
Examining Common Paradigms in Multi-Task Learning
Cathrin Elich, Lukas Kirchdorfer, Jan M. Köhler +1
While multi-task learning (MTL) has gained significant attention in recent years, its underlying mechanisms remain poorly understood. Recent methods did not yield consistent perfor…