To address this problem, we introduce the Model SEED, a web-based resource for high-throughput generation, optimization and analysis of genome-scale metabolic models.

Simplex optimization is one of the simplest algorithms available to train a neural network. Understanding how simplex optimization works, and how it compares to the more commonly used back-propagation ...

Edge inference engines often run a slimmed-down real-time engine that interprets a neural-network model, invoking kernels as it goes. But higher performance can be achieved by pre-compiling the model ...

The Transformer model uses optimization algorithms to adjust its parameters, improving its ability to differentiate between similar-sounding words like "rain" and "reign" in future transcriptions.

Chen Liang, Sankaran Mahadevan, Multidisciplinary Optimization under Uncertainty Using Bayesian Network, SAE International Journal of Materials and Manufacturing, Vol. 9, No. 2 (May 2016), pp. 419-429 ...

Network-level optimization is the most critical aspect of the world’s shared energy future. It gives utilities a holistic view of the energy landscape at any given moment, in real time.

When I asked WAN optimization veterans to weigh in on what they think will be the biggest technology and industry trends to watch during the year ahead, the economy (not surprisingly) played a ...