63 citations · 282 across the 11 of their papers we have counts for
11 papers
pgmpy: A Python Toolkit for Bayesian Networks
Ankur Ankan, Johannes Textor
Bayesian Networks (BNs) are used in various fields for modeling, prediction, and decision making. pgmpy is a python package that provides a collection of algorithms and tools to wo…
Combining Graphical and Algebraic Approaches for Parameter Identification in Latent Variable Structural Equation Models
Ankur Ankan, Inge Wortel, Kenneth A. Bollen +1
Measurement error is ubiquitous in many variables - from blood pressure recordings in physiology to intelligence measures in psychology. Structural equation models (SEMs) account f…
A Simple Unified Approach to Testing High-Dimensional Conditional Independences for Categorical and Ordinal Data
Ankur Ankan, Johannes Textor
Conditional independence (CI) tests underlie many approaches to model testing and structure learning in causal inference. Most existing CI tests for categorical and ordinal data st…
Reply to Comment on "Inverse Square Lévy Walks are not Optimal Search Strategies for d \geq 2 "
Nicolas Levernier, Johannes Textor, Olivier Bénichou +1
We refute here the concernes raised in the Comment of our letter. This reply states clearly the validity range of our results and shows that the optimality of inverse-square Levy w…
Inverse square Lévy walks are not optimal search strategies for
Nicolas Levernier, Olivier Benichou, Johannes Textor +1
The Lévy hypothesis states that inverse square Lévy walks are optimal search strategies because they maximise the encounter rate with sparse, randomly distributed, replenishable ta…
Separators and Adjustment Sets in Causal Graphs: Complete Criteria and an Algorithmic Framework
Benito van der Zander, Maciej Liśkiewicz, Johannes Textor
Principled reasoning about the identifiability of causal effects from non-experimental data is an important application of graphical causal models. This paper focuses on effects th…