4 citations · 9 across the 24 of their papers we have counts for
5 papers · 1 filter
Partitioning Time in Target Trial Emulation
Harold Tankpinou Zoumenou, Simon Ferreira, Charles Assaad +6
In target trial emulation, the treatment strategies that patients follow are inferred from the treatments they actually receive in routine care. However, in most settings, the outc…
Beyond Stationarity in Time Series: Discovering Causal Structures and Latent Regimes via Markov Blankets
Lei Zan, Charles K. Assaad, Emilie Devijver +1
This paper introduces Regime-aware Constraint-Based and Noise-Based causal discovery with Markov Blankets (RCBNB-MB), a novel causal discovery algorithm for time series that relaxe…
Root cause analysis via difference graph discovery from linear time-series data
Anouk Ruer, Timothée Loranchet, Daria Bystrova +1
Root cause analysis aims to identify the mechanisms responsible for anomalies in complex dynamical systems. In this paper, we study root cause analysis in linear time-series throug…
Missing data and cluster graphs: cluster-level missingness vs variable-level missingness
Willow Scott, Eugenio Valdano, Charles Assaad
Missing data is pervasive in many scientific domains such as public health, environmental science, and the social sciences. Recoverability from missing data is typically studied us…
Time Partitioning in Target Trial Emulation
Harold Tankpinou Zoumenou, Simon Ferreira, Charles Assaad +3
In target trial emulation, time partitioning enables researchers to handle time-varying confounders and immortal time bias with appropriate methods. Based on two clinical scenarios…