Machine Learning for Causal Inference
This book provides a deep understanding of the relationship between machine learning and causal inference. It covers a broad range of topics, starting with the preliminary foundations of causal inference, which include basic definitions, illustrative examples, and assumptions. It then delves into th...
| Other Authors: | , |
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| Format: | eBook |
| Language: | English |
| Published: |
Cham
Springer International Publishing
2023, 2023
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| Edition: | 1st ed. 2023 |
| Subjects: | |
| Online Access: | |
| Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
Table of Contents:
- Overview of the Book
- Causal Inference Preliminary
- Causal Effect Estimation: Basic Methodologies
- Causal Inference on Graphs
- Causal Effect Estimation: Recent Progress, Challenges, and Opportunities
- Fair Machine Learning Through the Lens of Causality
- Causal Explainable AI
- Causal Domain Generalization
- Causal Inference and Natural Language Processing
- Causal Inference and Recommendations
- Causality Encourage the Identifiability of Instance-Dependent Label Noise
- Causal Interventional Time Series Forecasting on Multi-horizon and Multi-series Data
- Continual Causal Effect Estimation
- Summary