Uncertainty is an intrinsic part of neural computation, whether for sensory processing, motor control or cognitive reasoning. For instance, it is impossible to determine with certainty the age of a ...
Revolutionary Analog-based Probabilistic Inference Devices for Unconventional Processing of Signals for Intelligent Data Exploitation. OK, so it’s no RADAR, SONAR or LASER (invented by the same folks ...
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Fully digital design paves the way for scalable probabilistic computing
Artificial intelligence and machine learning could become dramatically more efficient, thanks to a new type of computer ...
Alex Burmester does not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations beyond ...
The Virtual Brain Inference (VBI) toolkit enables efficient, accurate, and scalable Bayesian inference over whole-brain network models, improving parameter estimation, uncertainty quantification, and ...
Many organisms can predict future events from the statistics of past experience, but humans also excel at making predictions by pure reasoning: integrating multiple sources of information, guided by ...
A collaboration including the University of Oxford, University of British Columbia, Intel, New York University, CERN, and the National Energy Research Scientific Computing Center is working to make it ...
Many application domains, such as ecology or genomics, have to deal with multivariate non-Gaussian observations. A typical example is the joint observation of the respective abundances of a set of ...
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