Causal inference methods for supporting, understanding, and improving decision-making

Causal inference methods for supporting, understanding, and improving decision-making

<p>Causality and the ability to reason about cause-and-effect relationships are central to decision-making. This thesis contributes to the area of causal inference by proposing new machine learning methods that can be used for supporting, understanding, and improving decision-making, with a fo...

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Bibliografiske detaljer
Hovedforfatter:	Bica, I
Andre forfattere:	van der Schaar, M
Format:	Thesis
Sprog:	English
Udgivet:	2022
Fag:	Machine learning

Lignende værker

Interpretable causal systems: interpretability and causality in machine learning for human and nonhuman decision-making
af: Graham, L
Udgivet: (2020)

Large scale methods for kernels, causal inference and survival modelling
af: Hu, R
Udgivet: (2022)

Causal ML: Python package for causal inference machine learning
af: Yang Zhao, et al.
Udgivet: (2023-02-01)

Deep learning for causal inference on electronic health records
af: Rao, S
Udgivet: (2023)

Causal evidence in health decision making: methodological approaches of causal inference and health decision science
af: Kühne, Felicitas, et al.
Udgivet: (2022-12-01)

Intelligent Agents and Causal Inference: Enhancing Decision-Making through Causal Reasoning
af: Jairo Iván Vélez Bedoya, et al.
Udgivet: (2024-04-01)

Flexible and efficient simulation-based inference for models of decision-making
af: Jan Boelts, et al.
Udgivet: (2022-07-01)

Clinical decision making under uncertainty: a bootstrapped counterfactual inference approach
af: Hang Wu, et al.
Udgivet: (2024-09-01)

Transfer in sequential decision making
af: Luketina, J
Udgivet: (2023)

Causal inference and machine learning in endocrine epidemiology
af: Kosuke Inoue
Udgivet: (2024-10-01)

Enabling Decision Making with the Modified Causal Forest: Policy Trees for Treatment Assignment
af: Hugo Bodory, et al.
Udgivet: (2024-07-01)

Application and Prospects of Causal Inference in Microbiological Research
af: DOU Xin, LIU Yangtai, PEI Xiaoyan, DONG Qingli
Udgivet: (2023-05-01)

Machine Learning for Causal Inference in Biological Networks: Perspectives of This Challenge
af: Paola Lecca
Udgivet: (2021-09-01)

Decision-making support system for diagnosis of oncopathologies by histological images
af: Anatoliy Dovbysh, et al.
Udgivet: (2023-01-01)

Causality inference of nominal variables: A statistical simulation method
af: WenJun Zhang
Udgivet: (2021-12-01)

Transfering Targeted Maximum Likelihood Estimation for Causal Inference into Sports Science
af: Talko B. Dijkhuis, et al.
Udgivet: (2022-07-01)

Causal inference in AI education: A primer
af: Forney Andrew, et al.
Udgivet: (2022-07-01)

Improved decision making with similarity based machine learning: applications in chemistry
af: Dominik Lemm, et al.
Udgivet: (2023-01-01)

Simheuristics Approaches for Efficient Decision-Making Support in Materials Trading Networks
af: Markus Rabe, et al.
Udgivet: (2021-01-01)

Causal Inference in Threshold Regression and the Neural Network Extension (TRNN)
af: Yiming Chen, et al.
Udgivet: (2023-04-01)

Diabetes Prediction Through Linkage of Causal Discovery and Inference Model with Machine Learning Models
af: Mi Jin Noh, et al.
Udgivet: (2025-01-01)

Big Data, Data Science, and Causal Inference: A Primer for Clinicians
af: Yoshihiko Raita, et al.
Udgivet: (2021-07-01)

Understanding approximation for Bayesian inference in neural networks
af: Farquhar, S
Udgivet: (2022)

Machine learning coupled with causal inference to identify COVID-19 related chemicals that pose a high concern to drinking water
af: Min Han, et al.
Udgivet: (2024-02-01)

Intelligent Decision Support Systems—An Analysis of Machine Learning and Multicriteria Decision-Making Methods
af: Rahman Ali, et al.
Udgivet: (2023-11-01)

Optimization and imitation for pandemic policy and financial decision making
af: Fu, Y
Udgivet: (2023)

Detection of Decision-Making Manipulation in the Pairwise Comparison Method
af: Michał Strada, et al.
Udgivet: (2024-10-01)

Inferring the heterogeneous effect of urban land use on building height with causal machine learning
af: Yimin Chen, et al.
Udgivet: (2024-12-01)

Causality inference of linearly correlated variables: The statistical simulation and regression method
af: WenJun Zhang
Udgivet: (2021-12-01)

Learning and inference over relational data
af: Abboud, R
Udgivet: (2022)

Investigation of the Role of Machine Learning and Deep Learning in Improving Clinical Decision Making for Musculoskeletal Rehabilitation
af: Madhu Yadav, et al.
Udgivet: (2024-06-01)

Application of machine learning approaches in supporting irrigation decision making: A review
af: Lisa Umutoni, et al.
Udgivet: (2024-04-01)

Causal inference with marginal structural modeling for longitudinal data in laparoscopic surgery: A technical note
af: Zhongheng Zhang, et al.
Udgivet: (2022-12-01)

Neural networks for inference, inference for neural networks
af: Webb, S
Udgivet: (2018)

Research on a Decision Prediction Method Based on Causal Inference and a Multi-Expert FTOPJUDGE Mechanism
af: Qiang Zhao, et al.
Udgivet: (2022-06-01)

Data-Driven Surveillance: Effective Collection, Integration, and Interpretation of Data to Support Decision Making
af: Fernanda C. Dórea, et al.
Udgivet: (2021-03-01)

Predicting metabolic syndrome using decision tree and support vector machine methods
af: Farzaneh Karimi-Alavijeh, et al.
Udgivet: (2016-06-01)

A variant-informed decision support system for tackling COVID-19: a transfer learning and multi-attribute decision-making approach
af: Amirreza Salehi Amiri, et al.
Udgivet: (2024-09-01)

Deep transfer learning with Bayesian inference
af: Gambardella, A
Udgivet: (2021)

Evaluating Uses of Deep Learning Methods for Causal Inference
af: Albert Whata, et al.
Udgivet: (2022-01-01)