Ikuti
Massimiliano Lupo Pasini
Judul
Dikutip oleh
Dikutip oleh
Tahun
Analysis of Monte Carlo accelerated iterative methods for sparse linear systems
M Benzi, TM Evans, SP Hamilton, M Lupo Pasini, SR Slattery
Numerical Linear Algebra with Applications 24 (3), e2088, 2017
342017
Multi-task graph neural networks for simultaneous prediction of global and atomic properties in ferromagnetic systems
M Lupo Pasini, P Zhang, ST Reeve, JY Choi
Machine Learning: Science and Technology 3 (2), 025007, 2022
212022
Convergence analysis of Anderson‐type acceleration of Richardson's iteration
M Lupo Pasini
Numerical Linear Algebra with Applications 26 (4), e2241, 2019
212019
Fast and stable deep-learning predictions of material properties for solid solution alloys
M Lupo Pasini, YW Li, J Yin, J Zhang, K Barros, M Eisenbach
Journal of Physics: Condensed Matter 33 (8), 084005, 2020
192020
Scalable training of graph convolutional neural networks for fast and accurate predictions of HOMO-LUMO gap in molecules
JY Choi, P Zhang, K Mehta, A Blanchard, M Lupo Pasini
Journal of Cheminformatics 14 (70), https://trebuchet.public.springernature., 2022
132022
Deepspeed4science initiative: Enabling large-scale scientific discovery through sophisticated ai system technologies
SL Song, B Kruft, M Zhang, C Li, S Chen, C Zhang, M Tanaka, X Wu, ...
arXiv preprint arXiv:2310.04610, 2023
122023
A scalable algorithm for the optimization of neural network architectures
M Lupo Pasini, J Yin, YW Li, M Eisenbach
Parallel Computing 104, 102788, 2021
112021
HydraGNN
M Lupo Pasini, ST Reeve, P Zhang, JY Choi
https://doi.org/10.11578/dc.20211019.2 20211019, 2021
10*2021
Graph neural networks predict energetic and mechanical properties for models of solid solution metal alloy phases
M Lupo Pasini, GS Jung, S Irle
Computational Materials Science 224, 112141, 2023
72023
Two excited-state datasets for quantum chemical UV-vis spectra of organic molecules
M Lupo Pasini, K Mehta, P Yoo, S Irle
Nature Scientific Data 10 (546), 2023
72023
Anderson Acceleration for Distributed Training of Deep Learning Models
M Lupo Pasini, J Yin, V Reshniak, M Stoyanov
SoutheastCon 2022, 289-295, 2022
72022
Hierarchical model reduction driven by a proper orthogonal decomposition for parametrized advection-diffusion-reaction problems
M Lupo Pasini, S Perotto
Electronic transactions on numerical analysis ETNA 55, 187-212, 2022
72022
Fast and accurate predictions of total energy for solid solution alloys with graph convolutional neural networks
M Lupo Pasini, M Burc̆ul, ST Reeve, M Eisenbach, S Perotto
Smoky Mountains Computational Sciences and Engineering Conference, 79-98, 2021
62021
ORNL AISD-Ex: Quantum chemical prediction of UV/Vis absorption spectra for over 10 million organic molecules
ML Pasini, K Mehta, P Yoo, S Irle
52023
Stable Anderson Acceleration for Deep Learning
M Lupo Pasini, J Yin, V Reshniak, M Stoyanov
arXiv e-prints, arXiv: 2110.14813, 2021
5*2021
A Neural Network Approach to Predict Gibbs Free Energy of Ternary Solid Solutions
P Laiu, Y Yang, M Lupo Pasini, JY Choi, D Shin
Journal of Phase Equilibria and Diffusion 43, 916-930, 2022
42022
Scalable balanced training of conditional generative adversarial neural networks on image data
M Lupo Pasini, V Gabbi, J Yin, Perotto, Simona, N Laanait
Journal of Supercomputing 77 (11), 13358-13384, 2021
42021
A parallel strategy for density functional theory computations on accelerated nodes
M Lupo Pasini, B Turcksin, W Ge, JL Fattebert
Parallel Computing 100, 102703, 2020
42020
Anderson acceleration with approximate calculations: Applications to scientific computing
M Lupo Pasini, MP Laiu
Numerical Linear Algebra with Applications, e2562, 2024
32024
Deep learning workflow for the inverse design of molecules with specific optoelectronic properties
P Yoo, D Bhowmik, K Mehta, P Zhang, F Liu, M Lupo Pasini, S Irle
Scientific Reports 13 (1), 20031, 2023
32023
Sistem tidak dapat melakukan operasi ini. Coba lagi nanti.
Artikel 1–20