Conveners
Data Processing in High Energy Physics
- Václav Kůs (KM FJFI CVUT)
Fast detector simulations have been of interest in the high energy physics community because of the increasing data intake. Among different deep learning techniques, transformer networks stand out thanks to the lack of inductive bias and their potential to learn complex data structures. We present a study on representation learning of transformers using the calorimeter showers and an image...
In high-energy physics, detecting rare events and computing their properties demand precise and reliable statistical methods, with uncertainty quantification being crucial. Today, most research relies on machine learning methods, where calibrating output probabilities can be complex. How can we then draw conclusions with the required five sigma statistical significance, which is essential for...
