Concr CEO Irina Babina and CTO Matthew Griffiths unpack how Bayesian foundation models can excel at uncertainty management to ...
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A better method for identifying overconfident large language models
Large language models (LLMs) can generate credible but inaccurate responses, so researchers have developed uncertainty quantification methods to check the reliability of predictions. One popular ...
A new technical paper titled “Bringing uncertainty quantification to the extreme-edge with memristor-based Bayesian neural networks” was published by researchers at Université Grenoble Alpes, CEA, ...
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Although artificial intelligence (AI) has demonstrated potential in automating glaucoma screening, there is still a ...
Bayesian networks, also known as Bayes nets, belief networks, or decision networks, are a powerful tool for understanding and reasoning about complex systems under uncertainty. They are essentially ...
I am a Postdoctoral Research Associate working on the NERC funded project “Aerosol-MFR: Towards Maximum Feasible Reduction in Aerosol Forcing Uncertainty”, working with Dr Jill Johnson and Prof Jeremy ...
The Uncertainty Engine is guiding research in fusion plasma physics. Could similar approaches benefit fission research as ...
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