Nature

Fine-tuning foundation models of materials interatomic potentials with frozen transfer learning

Machine-learned interatomic potentials are revolutionising atomistic materials simulations by providing accurate and scalable predictions within the scope covered by the training data. However, ...
Nature

Machine learning based prediction for bulk porosity and static elastic modulus of Yungang Grottoes sandstone

In this work, four mainstream machine learning (ML) techniques are used to evaluate the bulk porosity and static elastic modulus of weathered Yungang Grottoes sandstone. Datasets are gathered from the ...
Insider Monkey

Elastic N.V. (ESTC) Unveils ‘Better Binary Quantization’ to Enhance Elasticsearch for AI and Machine Learning Data Processing

We recently compiled a list of the 15 AI News That Should Not Be Ignored. In this article, we are going to take a look at where Elastic N.V. (NYSE:ESTC) stands against the other AI stocks that should ...
International Monetary Fund

GDP Nowcasting Performance of Traditional Econometric Models vs Machine-Learning Algorithms: Simulation and Case Studies

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...