20240917-1350

Using ensemble learning to improve radiation tolerance of CNNs in space applications

With the increasing complexity of space missions, improving the resilience of AI systems against radiation-induced errors is critical. This paper proposes the use of application-level optimizations of Convolutional Neural Network (CNN)-based systems to improve robustness in space applications without relying… Read More »Using ensemble learning to improve radiation tolerance of CNNs in space applications

Enhancing Solar Driver Forecasting with Multivariate Transformers

In this work, we develop a comprehensive framework for F10.7, S10.7, M10.7, and Y10.7 solar driver forecasting with a time series Transformer (PatchTST). To ensure an equal representation of high and low levels of solar activity, we construct a custom… Read More »Enhancing Solar Driver Forecasting with Multivariate Transformers