3 citations · 3 across the 2 of their papers we have counts for
5 papers
ENFORCE: Nonlinear Constrained Learning with Adaptive-depth Neural Projection
Giacomo Lastrucci, Artur M. Schweidtmann
Ensuring neural networks adhere to domain-specific constraints is crucial for addressing safety and trustworthiness while also enhancing inference accuracy. Despite the nonlinear n…
Pruning for efficient deterministic global optimization over trained ReLU neural networks
Giacomo Lastrucci, Tanuj Karia, Victor Schulte +2
Neural networks are increasingly used as surrogates in optimization problems to replace computationally expensive models. However, embedding ReLU neural networks in mathematical pr…
Text2Model: Generating dynamic chemical reactor models using large language models (LLMs)
Sophia Rupprecht, Yassine Hounat, Monisha Kumar +2
As large language models have shown remarkable capabilities in conversing via natural language, the question arises as to how LLMs could potentially assist chemical engineers in re…
Deterministic Global Optimization over trained Kolmogorov Arnold Networks
Tanuj Karia, Giacomo Lastrucci, Artur M. Schweidtmann
To address the challenge of tractability for optimizing mathematical models in science and engineering, surrogate models are often employed. Recently, a new class of machine learni…
Picard-KKT-hPINN: Enforcing Nonlinear Enthalpy Balances for Physically Consistent Neural Networks
Giacomo Lastrucci, Tanuj Karia, Zoë Gromotka +1
Neural networks are widely used as surrogate models but they do not guarantee physically consistent predictions thereby preventing adoption in various applications. We propose a me…