Overview: Clear problem definitions prevent wasted effort and keep machine learning work focused.Clean, well-understood data ...
Jessica Lin and Zhenqi (Pete) Shi from Genentech describe a novel machine learning approach to predicting retention times for ...
This study presents SynaptoGen, a differentiable extension of connectome models that links gene expression, protein-protein interaction probabilities, synaptic multiplicity, and synaptic weights, and ...
A research team led by Chang Keke from the Ningbo Institute of Materials Technology and Engineering (NIMTE), Chinese Academy ...
eSpeaks’ Corey Noles talks with Rob Israch, President of Tipalti, about what it means to lead with Global-First Finance and how companies can build scalable, compliant operations in an increasingly ...
Manufacturing technologies have been the first domain to experience this transformation. The review documents how artificial ...
In food drying applications, machine learning has demonstrated strong capability in predicting drying rates, moisture ...
As data privacy collides with AI’s rapid expansion, the Berkeley-trained technologist explains how a new generation of models is learning without crossing ethical lines.
Theoretical physicists use machine-learning algorithms to speed up difficult calculations and eliminate untenable theories—but could they transform what it means to make discoveries? Theoretical ...
Adam M. Root argues businesses must anchor ML in customer problems, not technology. He details a strategy using ...
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