Zobrazeno 1 - 10
of 2 872
pro vyhledávání: '"Salazar, Luis A."'
With the establishment of machine learning (ML) techniques in the scientific community, the construction of ML potential energy surfaces (ML-PES) has become a standard process in physics and chemistry. So far, improvements in the construction of ML-P
Externí odkaz:
http://arxiv.org/abs/2407.15175
Uncertainty quantification (UQ) to detect samples with large expected errors (outliers) is applied to reactive molecular potential energy surfaces (PESs). Three methods - Ensembles, Deep Evidential Regression (DER), and Gaussian Mixture Models (GMM)
Externí odkaz:
http://arxiv.org/abs/2402.17686
The structure and dynamics of a molecular system is governed by its potential energy surface (PES), representing the total energy as a function of the nuclear coordinates. Obtaining accurate potential energy surfaces is limited by the exponential sca
Externí odkaz:
http://arxiv.org/abs/2309.16491
Full dimensional potential energy surfaces (PESs) based on machine learning (ML) techniques provide means for accurate and efficient molecular simulations in the gas- and condensed-phase for various experimental observables ranging from spectroscopy
Externí odkaz:
http://arxiv.org/abs/2304.12973
Artificial Neural Networks (ANN) are already heavily involved in methods and applications for frequent tasks in the field of computational chemistry such as representation of potential energy surfaces (PES) and spectroscopic predictions. This perspec
Externí odkaz:
http://arxiv.org/abs/2209.11581
Autor:
Töpfer, Kai, Pasti, Andrea, Das, Anuradha, Salehi, Seyedeh Maryam, Vazquez-Salazar, Luis Itza, Rohrbach, David, Feurer, Thomas, Hamm, Peter, Meuwly, Markus
The spectroscopy and structural dynamics of a deep eutectic mixture (KSCN/acetamide) with varying water content is investigated from 2D IR (with the C-N stretch vibration of the SCN$^-$ anions as the reporter) and THz spectroscopy. Molecular dynamics
Externí odkaz:
http://arxiv.org/abs/2207.08529
The value of uncertainty quantification on predictions for trained neural networks (NNs) on quantum chemical reference data is quantitatively explored. For this, the architecture of the PhysNet NN was suitably modified and the resulting model was eva
Externí odkaz:
http://arxiv.org/abs/2207.06916
Autor:
Blanco, Miriam, Miranda, Carmen, Vecino, Raquel, Eizaguirre, Javier, García Calatayud, Salvador, Juste, Mercedes, Sánchez Valverde, Felix, Guardiola, Antonio, Díaz, Xavier, Ribes, Carmen, Polanco, Isabel, Román, Enriqueta, Barrio, Josefa, Cilleruelo, María Luz, Torres, Ricardo, Almazán, Vega, Coronel, Cristobal, Espín, Beatriz, Martínez-Ojinaga, Eva, Pérez Solís, David, Moreno, María Antonia, Reyes, Joaquín, Fernández Salazar, Luis, Farrais, Sergio, Castillejo, Gemma, Fontanillas, Noelia, Noguerol, Mar, Prieto, Alicia, Donat, Ester
Publikováno v:
In Anales de Pediatria October 2024 101(4):267-277
Autor:
Garcia-Ballestas, Ezequiel, Villafañe, Javier, Nuñez-Baez, Karen, Florez Perdomo, William A., Duran, Miguel A., Janjua, Tariq, Moscote-Salazar, Luis Rafael, Agrawal, Amit
Publikováno v:
In Clinical Neurology and Neurosurgery October 2024 245
Autor:
Guevara-Cruz, Martha, Hernández-Gómez, Karla G., Condado-Huerta, Citlally, González-Salazar, Luis E., Peña-Flores, Ana Karen, Pichardo-Ontiveros, Edgar, Serralde-Zúñiga, Aurora E., Sánchez-Tapia, Mónica, Maya, Otoniel, Medina-Vera, Isabel, Noriega, Lilia G., López-Barradas, Adriana, Rodríguez-Lima, Oscar, Mata, Irma, Olin–Sandoval, Viridiana, Torres, Nimbe, Tovar, Armando R., Velázquez-Villegas, Laura A.
Publikováno v:
In Clinical Nutrition August 2024 43(8):1914-1928