4 papers
Higgs Production Classifier using Weak Supervision
Kai-Feng Chen, Yi-An Chen, Cheng-Wei Chiang +1
A reliable determination of the Higgs production mechanism in hadron collider experiments is essential in the program of the measurements of the Higgs couplings. We employ weak sup…
Enhancing the Sensitivity for Triple Higgs Boson Searches with Deep Learning Techniques
Cheng-Wei Chiang, Feng-Yang Hsieh, Shih-Chieh Hsu +2
Using two benchmark models containing extended scalar sectors beyond the Standard Model, we study deep learning techniques to enhance the sensitivity of resonant triple Higgs boson…
Improving the performance of weak supervision searches using data augmentation
Zong-En Chen, Cheng-Wei Chiang, Feng-Yang Hsieh
Weak supervision combines the advantages of training on real data with the ability to exploit signal properties. However, training a neural network using weak supervision often req…
Deep Learning to Improve the Sensitivity of Di-Higgs Searches in the Channel
Cheng-Wei Chiang, Feng-Yang Hsieh, Shih-Chieh Hsu +1
The study of di-Higgs events, both resonant and non-resonant, plays a crucial role in understanding the fundamental interactions of the Higgs boson. In this work we consider di-Hig…