Information Theory: A Tutorial Introduction
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Abstract (arXiv)
Shannon's mathematical theory of communication defines fundamental limits on how much information can be transmitted between the different components of any man-made or biological system. This paper is an informal but rigorous introduction to the main ideas implicit in Shannon's theory. An annotated reading list is provided for further reading.
Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). First posted on arXiv 16 Feb 2018.
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Citing papers per year: 2022: 2; 2023: 1; 2024: 1; 2025: 2; 2026: 1.
7 papers.
- 2023What Makes for Robust Multi-Modal Models in the Face of Missing Modalities?cited by 5
- 2024Strong Transitivity Relations and Graph Neural Networkscited by 3
- 2026The Rate-Distortion-Polysemanticity Tradeoff in SAEscited by 3
- 2022NECA: Network-Embedded Deep Representation Learning for Categorical Datacited by 0
- 2022Finding Patterns in Visualized Data by Adding Redundant Visual Informationcited by 0
- 2025Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturingcited by 0
- 2025Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimizationcited by 0
- 2026The Rate-Distortion-Polysemanticity Tradeoff in SAEs14 May 2026
- 2025Synergizing Reinforcement Learning and Genetic Algorithms for Neural Combinatorial Optimization11 Jun 2025
- 2025Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing30 Apr 2025
- 2024Strong Transitivity Relations and Graph Neural Networks1 Jan 2024
- 2023What Makes for Robust Multi-Modal Models in the Face of Missing Modalities?10 Oct 2023
- 2022Finding Patterns in Visualized Data by Adding Redundant Visual Information27 May 2022
- 2022NECA: Network-Embedded Deep Representation Learning for Categorical Data25 May 2022