Massimiliano Lupo Pasini | DeepAI

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Featured Co-authors

Pei Zhang
22 publications
Junqi Yin
14 publications
Nicola Ferro
14 publications
Simona Perotto
13 publications
Markus Eisenbach
9 publications
Yuanyuan Zhao
8 publications
M. Paul Laiu
6 publications
Kshitij Mehta
5 publications
Jong Youl Choi
5 publications
Miroslav Stoyanov
4 publications
Viktor Reshniak
4 publications

∙ 10/07/2022

A deep learning approach to solve forward differential problems on graphs

We propose a novel deep learning (DL) approach to solve one-dimensional ...

0 Yuanyuan Zhao, et al. ∙

∙ 10/07/2022

A deep learning approach for detection and localization of leaf anomalies

The detection and localization of possible diseases in crops are usually...

0 Davide Calabrò, et al. ∙

∙ 07/25/2022

Stable Parallel Training of Wasserstein Conditional Generative Adversarial Neural Networks

We propose a stable, parallel approach to train Wasserstein Conditional ...

0 Massimiliano Lupo Pasini, et al. ∙

∙ 07/22/2022

Scalable training of graph convolutional neural networks for fast and accurate predictions of HOMO-LUMO gap in molecules

Graph Convolutional Neural Network (GCNN) is a popular class of deep lea...

0 Jong Youl Choi, et al. ∙

∙ 06/08/2022

Anderson acceleration with approximate calculations: applications to scientific computing

We provide rigorous theoretical bounds for Anderson acceleration (AA) th...

0 Massimiliano Lupo Pasini, et al. ∙

∙ 04/01/2022

Hierarchical model reduction driven by machine learning for parametric advection-diffusion-reaction problems in the presence of noisy data

We propose a new approach to generate a reliable reduced model for a par...

0 Massimiliano Lupo Pasini, et al. ∙

∙ 02/04/2022

Multi-task graph neural networks for simultaneous prediction of global and atomic properties in ferromagnetic systems

We introduce a multi-tasking graph convolutional neural network, HydraGN...

0 Massimiliano Lupo Pasini, et al. ∙

∙ 10/26/2021

Stable Anderson Acceleration for Deep Learning

Anderson acceleration (AA) is an extrapolation technique designed to spe...

0 Massimiliano Lupo Pasini, et al. ∙

∙ 02/21/2021

Scalable Balanced Training of Conditional Generative Adversarial Neural Networks on Image Data

We propose a distributed approach to train deep convolutional generative...

3 Massimiliano Lupo Pasini, et al. ∙

∙ 09/07/2019

A greedy constructive algorithm for the optimization of neural network architectures

In this work we propose a new method to optimize the architecture of an ...

0 Massimiliano Lupo Pasini, et al. ∙

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