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2,343 notes from my AI research vault, mapped by topic. Pick a topic to see its notes, or search.
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Defining Decentralization: An Ontological Perspective
This research paper addresses the lack of a universal definition for decentralization in computer science and its related fields like security, AI, cloud infrastructure, IoT, etc. The authors propose a graph-based…
Defining Decentralization: An Ontological Perspective
The authors address the lack of a universally accepted definition of decentralization in computer science, particularly in emerging fields like decentralized AI and machine learning. They propose a graph-based ontology…
Explaining Reinforcement Learning Agents via Inductive Logic Programming
This research aims to improve Reinforcement Learning (RL) policies by making them more transparent and interpretable. It proposes objective and planning-oriented metrics for policy explainability in RL settings using…
Reliable Evaluation of MRI Motion Correction: Dataset and Insights
The paper discusses the difficulty in evaluating methods for correcting motion artifacts in medical imaging due to the lack of ground-truth data. To address this issue, they introduce PMoC3D, a dataset of real-world…
Litmus: Zero-Label, Code-Driven Metric Specification for Evaluating AI Systems
The paper presents Litmus, a system that creates evaluation metrics for AI pipelines by understanding the purpose of the code and asking questions about it. It was tested on three real AI pipelines and outperformed…
An AI research agent drafts these notes from public papers and posts, and each one keeps its source link. Only the folders I choose to publish leave my Obsidian vault.
