LATTE: an atomic environment descriptor based on Cartesian tensor contractions

no code implementations • 13 May 2024 • Franco Pellegrini, Stefano de Gironcoli, Emine Küçükbenli

We propose a new descriptor for local atomic environments, to be used in combination with machine learning models for the construction of interatomic potentials.

PANNA 2.0: Efficient neural network interatomic potentials and new architectures

1 code implementation • 19 May 2023 • Franco Pellegrini, Ruggero Lot, Yusuf Shaidu, Emine Küçükbenli

We present the latest release of PANNA 2. 0 (Properties from Artificial Neural Network Architectures), a code for the generation of neural network interatomic potentials based on local atomic descriptors and multilayer perceptrons.

Efficient Neural Network

Sifting out the features by pruning: Are convolutional networks the winning lottery ticket of fully connected ones?

1 code implementation • 27 Apr 2021 • Franco Pellegrini, Giulio Biroli

Our results show that the winning lottery tickets of FCNs display the key features of CNNs.

Inductive Bias

An analytic theory of shallow networks dynamics for hinge loss classification

1 code implementation • NeurIPS 2020 • Franco Pellegrini, Giulio Biroli

Neural networks have been shown to perform incredibly well in classification tasks over structured high-dimensional datasets.

General Classification