collaborators

5 papers

cs.MA2026

CausalSteward: An Agentic Divide-Conquer-Combine Copilot for Causal Discovery

Nicholas Tagliapietra, Gian Lorenzo Marchioni, Moritz Willig +3

Learning causal models from high-dimensional data is a significant challenge, particularly in real-world settings where violations of core assumptions lead to causal identifiabilit…

cs.LG2026

StableRCA: Robust Graph-Agnostic Mechanism-Level Root Cause Analysis

Xiaoyu Lin, Nicholas Tagliapietra, Kehan Li +2

Root-Cause Analysis (RCA) seeks to identify the variables responsible for abnormal system behavior in complex domains such as manufacturing, cloud computing, and healthcare. Existi…

cs.AI2026

ORCA: An End-to-End Interactive Copilot for Optimized Root Cause Analysis

Phi Nguyen Xuan, Nicholas Tagliapietra, Lavdim Halilaj +2

Causal analysis is a crucial task in many domains, including manufacturing, social science, and medicine. However, despite recent progress, the conceptual and methodological comple…

cs.LG2025

Causal Structure Learning for Dynamical Systems with Theoretical Score Analysis

Nicholas Tagliapietra, Katharina Ensinger, Christoph Zimmer +1

Real world systems evolve in continuous-time according to their underlying causal relationships, yet their dynamics are often unknown. Existing approaches to learning such dynamics…

cs.LG2025

CausalMan: A physics-based simulator for large-scale causality

Nicholas Tagliapietra, Juergen Luettin, Lavdim Halilaj +3

A comprehensive understanding of causality is critical for navigating and operating within today's complex real-world systems. The absence of realistic causal models with known dat…