12 papers
A Unified Approach to Interpretable Causal Root Cause Attribution
Jing Zhou, Dominik Janzing, Sepp Tsang +2
Understanding why a target metric changes is a fundamental problem in data-driven decision making, beyond anomaly detection alone. We study root cause attribution for metric change…
Falsifying Causal Graphs With Outlier Events
William Roy Orchard, Philipp M. Faller, Dominik Janzing
True causal relationships are rarely known, and inferring causal graphs from data is hard. A fundamental challenge is how to assess whether a given causal graph is good in the abse…
NetCause: Counterfactual Learning for Root Cause Analysis in Large-Scale Networks
Fabien Chraim, Jian Zhang, Dominik Janzing +3
Can a learned model capture how faults propagate through a large-scale network and use this knowledge to causally attribute customer impact to its underlying root cause? Existing r…
Graphical Causal Reasoning for Root Cause Analysis in Cloud Networks
Fabien Chraim, Dominik Janzing, John Evans
Cloud-computing relies on large-scale networks which are inherently complex systems. In this paper, we present a novel approach to root cause analysis (RCA) of cloud network incide…
Measuring Semantic Progress in Multi-turn Dialogue via Information Gain
Paul He, Shiva Kasiviswanathan, Dominik Janzing
Evaluating multi-turn dialogue is challenging because quality emerges across turns rather than within individual responses. We focus on a key dimension of information-seeking dialo…
Evaluating Bivariate Causal Statements Based on Mutual Compatibility
Erik Jahn, Dominik Janzing
For many real-world systems, causal ground truth is difficult to obtain, making claims about causal effects hard to assess. We develop methods for evaluating collections of $\binom…