Category: Information Technology
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Stats don’t show enough
Same Stats, Different Graphs: Generating Datasets with Varied Appearance and Identical Statistics through Simulated Annealing has some great figures I want to share. They show datasets which are identical over a number of statistical properties, yet produce dissimilar graphs, are frequently used to illustrate the importance of graphical representations when exploring data. As a geo-scientists,…
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Language influences perception and concept formation
A neurobiologically constrained model of semantic learning in the human brain was used to simulate the acquisition of concrete and abstract concepts, either with or without verbal labels. Concept acquisition and semantic learning were simulated using Hebbian learning mechanisms. The network’s category learning performance is defined as the extent to which it successfully: (i) grouped…
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“CAUSEME” to benchmark causal methods
The heart of the scientific enterprise is a rational effort to understand the causes behind the phenomena we observe. In large-scale complex dynamical systems such as the Earth system, real experiments are rarely feasible. However, a rapidly increasing amount of observational and simulated data opens up the use of novel data-driven causal methods beyond the…
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Designing Ecosystems of Intelligence from First Principles
Karl Friston joins VERSES as Chief Scientist to Lead New Era in Artificial Intelligence.VERSES published its research paper to arxiv.org to explore the applications and implications of Active Inference on the future of Artificial Intelligence. “Designing Ecosystems of Intelligence from First Principles” lays out a vision of research and development in the field of artificial intelligence…
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Statistical inference links data and theory in network science
The number of network science applications across many different fields has been rapidly increasing. Surprisingly, the development of theory and domain-specific applications often occur in isolation, risking an effective disconnect between theoretical and methodological advances and the way network science is employed in practice. . In this work, we will focus on three intimately related…
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Information theory: A foundation for complexity science
Amos Golan and John Harte published a perspective paper, consolidating the insights and research on knowledge and models from incomplete information in complex environments, based on MaxEnt Modeling and inference are central to most areas of science and especially to evolving and complex systems. Critically, the information we have is often uncertain and insufficient, resulting…
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Technology readiness levels for machine learning systems
The development and deployment of machine learning systems can be executed easily with modern tools, but the process is typically rushed and means-to-an-end. Lack of diligence can lead to technical debt, scope creep and misaligned objectives, model misuse and failures, and expensive consequences. Engineering systems, on the other hand, follow well-defined processes and testing standards…
