opennn

Сравнение нескольких способов представления слов для построения языковых моделей

Artificial Neural Network Intelligence

Reproduction code for a router that projects samples onto nonlinear, discrete, and output-coupled constraints over a frozen neural-network surrogate — feasible-by-construction optimization over NN surrogates, benchmarked on real-world data

The Biosphere was not built because we could. It was built because we had to.

Neural network response optimization via Iterative Domain Contraction (IDC). We present a derivative-free optimization framework for determining optimal operating conditions of systems modeled by trained neural networks.

Reproducibility code for the RIAI 2026 article by S. Scala & R. López on inverse design with surrogate neural networks, regenerates every figure, table and number: feasible-manifold recovery under equality constraints, mixed-sense objectives, and Jacobian robustness selection (CNC AISI H13 + high-entropy-alloy hardness).

Reproduction code, data, and manuscript for "Diseño industrial óptimo con redes neuronales" (SCI 2026): derivative-free optimization of neural-network surrogates with Iterative Domain Contraction (IDC), on OPV photostability and yacht-hull design.