CAnDOIT: Causal Discovery with Observational and Interventional Data
from Time-Series

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CAnDOIT: Causal Discovery with Observational and Interventional Data from Time-Series

3 October 2024

Nicola Bellotto

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Papers citing "CAnDOIT: Causal Discovery with Observational and Interventional Data from Time-Series"

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Title
Causality-enhanced Decision-Making for Autonomous Mobile Robots in Dynamic Environments Luca Castri Gloria Beraldo Nicola Bellotto 90 0 0 16 Apr 2025
Enhancing Causal Discovery from Robot Sensor Data in Dynamic Scenarios Luca Castri Sariah Mghames Marc Hanheide Nicola Bellotto CML 64 13 0 20 Feb 2023
Learning Temporally Causal Latent Processes from General Temporal Data Weiran Yao Yuewen Sun Alex Ho Changyin Sun Kun Zhang BDL CML 97 87 0 11 Oct 2021
Efficient Neural Causal Discovery without Acyclicity Constraints Phillip Lippe Taco S. Cohen E. Gavves CML 73 72 0 22 Jul 2021
Disentanglement via Mechanism Sparsity Regularization: A New Principle for Nonlinear ICA Sébastien Lachapelle Pau Rodríguez López Yash Sharma Katie Everett Rémi Le Priol Alexandre Lacoste Simon Lacoste-Julien CML OOD 102 141 0 21 Jul 2021
High-recall causal discovery for autocorrelated time series with latent confounders Andreas Gerhardus J. Runge CML AI4TS 86 102 0 03 Jul 2020
Discovering contemporaneous and lagged causal relations in autocorrelated nonlinear time series datasets Jakob Runge 86 194 0 07 Mar 2020
Physics-Constrained Deep Learning for High-dimensional Surrogate Modeling and Uncertainty Quantification without Labeled Data Yinhao Zhu N. Zabaras P. Koutsourelakis P. Perdikaris PINN AI4CE 121 871 0 18 Jan 2019