The identities or bounds that relate information measures (e.g., the entropy and mutual information) and estimation measures (e.g., the minimum means square error ...
Information theory provides a mathematical framework for quantifying information and uncertainty, forming the backbone of modern communication, signal processing, and data analysis. Central to this ...
To understand complex brain processes, there is a clear need to shift from traditional single-cell studies of trial-averaged responses to single-trial analyses of multiple neurons. In this respect, ...
Information theory addresses the fundamental mathematical limits of communication (error correction), compression, and security, built upon probability theory. This ...
Tim Bayne is affiliated with the Canadian Institute for Advanced Research (CIFAR). Science is hard. The science of consciousness is particularly hard, beset with philosophical difficulties and a ...
In a video from the early 1950s, Bell Labs scientist Claude Shannon demonstrates one of his new inventions: a toy mouse named Theseus that looks like it could be a wind-up. The gaunt Shannon, looking ...
DO YOU THINK that your newest acquisition, a Roomba robotic vacuum cleaner that traces out its unpredictable paths on your living room floor, is conscious? What about that bee that hovers above your ...
A new idea called the “information bottleneck” is helping to explain the puzzling success of today’s artificial-intelligence algorithms — and might also explain how human brains learn. Even as ...
Like a brain, a deep neural network has layers of neurons—artificial ones that are figments of computer memory. When a neuron fires, it sends signals to connected neurons in the layer above. During ...
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