1 citations · 1 across the 6 of their papers we have counts for
7 papers
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…
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…
Constraint-based difference graph discovery in a linear setting
Daria Bystrova, Emilie Devijver
Comparing causal relationships across populations is essential in many scientific domains. This paper studies the problem of inferring a difference graph between two environments a…
Prior-Data Fitted Networks for Causal Inference: a Simulation Study with Real-World Scenarios
Francisco Mourao, David Hajage, Daria Bystrova +4
Prior-Data Fitted Networks (PFNs) represent a paradigm shift in tabular data prediction. We present the principles of this new paradigm and evaluate two PFNs for estimating the ave…
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…
Causal Discovery from Time Series with Hybrids of Constraint-Based and Noise-Based Algorithms
Daria Bystrova, Charles K. Assaad, Julyan Arbel +3
Constraint-based methods and noise-based methods are two distinct families of methods proposed for uncovering causal graphs from observational data. However, both operate under str…
Bayesian mixture models (in)consistency for the number of clusters
Louise Alamichel, Daria Bystrova, Julyan Arbel +1
Bayesian nonparametric mixture models are common for modeling complex data. While these models are well-suited for density estimation, recent results proved posterior inconsistency…