Carmelo Gonzales

According to our database, Carmelo Gonzales authored at least 7 papers between 2023 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Ensembles of Neural Surrogates for Parametric Sensitivity in Ocean Modeling.

Yixuan Sun, Romain Egele, Sri Hari Krishna Narayanan, Luke Van Roekel, Carmelo Gonzales, Steven Brus, Balu Nadiga, Sandeep Madireddy, Prasanna Balaprakash

CoRR, August, 2025

Evaluating Universal Machine Learning Force Fields Against Experimental Measurements.

Sajid Mannan, Vaibhav Bihani, Carmelo Gonzales, Kin Long Kelvin Lee, Nitya Nand Gosvami, Sayan Ranu, Santiago Miret, N. M. Anoop Krishnan

CoRR, August, 2025

Energy & Force Regression on DFT Trajectories is Not Enough for Universal Machine Learning Interatomic Potentials.

Santiago Miret, Kin Long Kelvin Lee, Carmelo Gonzales, Sajid Mannan, N. M. Anoop Krishnan

CoRR, February, 2025

2023

The Open MatSci ML Toolkit: A Flexible Framework for Machine Learning in Materials Science.

Santiago Miret, Kin Long Kelvin Lee, Carmelo Gonzales, Marcel Nassar, Matthew Spellings

Trans. Mach. Learn. Res., 2023

MatSciML: A Broad, Multi-Task Benchmark for Solid-State Materials Modeling.

Kin Long Kelvin Lee, Carmelo Gonzales, Marcel Nassar, Matthew Spellings, Mikhail Galkin, Santiago Miret

CoRR, 2023

Using Multiple Vector Channels Improves E(n)-Equivariant Graph Neural Networks.

Daniel T. Levy, Sékou-Oumar Kaba, Carmelo Gonzales, Santiago Miret, Siamak Ravanbakhsh

CoRR, 2023

Towards Foundation Models for Materials Science: The Open MatSci ML Toolkit.

Kin Long Kelvin Lee, Carmelo Gonzales, Matthew Spellings, Mikhail Galkin, Santiago Miret, Nalini Kumar

Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, 2023