6 citations · 6 across the 2 of their papers we have counts for
4 papers
Supervised deep learning prediction of the formation enthalpy of the full set of configurations in complex phases: the phase as an example
Jean-Claude Crivello, Nataliya Sokolovska, Jean-Marc Joubert
Machine learning (ML) methods are becoming integral to scientific inquiry in numerous disciplines, such as material sciences. In this manuscript, we demonstrate how ML can be used…
CrystalGAN: Learning to Discover Crystallographic Structures with Generative Adversarial Networks
Asma Nouira, Nataliya Sokolovska, Jean-Claude Crivello
Our main motivation is to propose an efficient approach to generate novel multi-element stable chemical compounds that can be used in real world applications. This task can be form…
Disease Classification in Metagenomics with 2D Embeddings and Deep Learning
Thanh Hai Nguyen, Edi Prifti, Yann Chevaleyre +2
Deep learning (DL) techniques have shown unprecedented success when applied to images, waveforms, and text. Generally, when the sample size () is much bigger than the number of…
Deep Learning for Metagenomic Data: using 2D Embeddings and Convolutional Neural Networks
Thanh Hai Nguyen, Yann Chevaleyre, Edi Prifti +2
Deep learning (DL) techniques have had unprecedented success when applied to images, waveforms, and texts to cite a few. In general, when the sample size (N) is much greater than t…