Ensemble framework for causality learning with heterogeneous directed acyclic graphs through the lens of optimization
Abstract Directed Acyclic Graphs (DAGs) are informative graphical outputs of causal
learning algorithms to visualize the causal structure among variables. In practice, different …
learning algorithms to visualize the causal structure among variables. In practice, different …
A data-driven two-phase multi-split causal ensemble model for time series
Causal inference is a fundamental research topic for discovering the cause–effect
relationships in many disciplines. Inferring causality means identifying asymmetric relations …
relationships in many disciplines. Inferring causality means identifying asymmetric relations …
[HTML][HTML] Pairwise causal discovery with support measure machines
Bivariate causal discovery amounts to inferring the causal association between two random
variables, usually from observational data. This task is the simplest and most fundamental …
variables, usually from observational data. This task is the simplest and most fundamental …
Bootstrap aggregation and confidence measures to improve time series causal discovery
Learning causal graphs from multivariate time series is an ubiquitous challenge in all
application domains dealing with time-dependent systems, such as in Earth sciences …
application domains dealing with time-dependent systems, such as in Earth sciences …
[PDF][PDF] Towards Extracting Causal Graph Structures from TradeData and Smart Financial Portfolio Risk Management.
P Ravivanpong, T Riedel, P Stock - EDBT/ICDT Workshops, 2022 - ceur-ws.org
Risk managers of asset management companies monitor portfolio risk metrics such as the
Value at Risk in order to analyze and to communicate the risks timely to portfolio managers …
Value at Risk in order to analyze and to communicate the risks timely to portfolio managers …
A Weighted Ensemble Causal Discovery Method for Effective Connectivity Estimation
Q Zhang, Y Zhang, Y Ding, Y Chen… - 2023 IEEE Smart …, 2023 - ieeexplore.ieee.org
Exploring and explaining the effective connectivity (EC) between brain regions can help us
understand the mechanisms behind neurodegenerative diseases such as Alzheimer's …
understand the mechanisms behind neurodegenerative diseases such as Alzheimer's …
Large-Scale Causality Discovery Analytics as a Service
Data-driven causality discovery is a common way to understand causal relationships among
different components of a system. We study how to achieve scalable data-driven causality …
different components of a system. We study how to achieve scalable data-driven causality …