9 citations · 16 across the 4 of their papers we have counts for
5 papers
TrackFormers: In Search of Transformer-Based Particle Tracking for the High-Luminosity LHC Era
Sascha Caron, Nadezhda Dobreva, Antonio Ferrer Sánchez +5
High-Energy Physics experiments are facing a multi-fold data increase with every new iteration. This is certainly the case for the upcoming High-Luminosity LHC upgrade. Such increa…
Quantum Active Learning
Yongcheng Ding, Yue Ban, Mikel Sanz +2
Quantum machine learning, as an extension of classical machine learning that harnesses quantum mechanics, facilitates effiient learning from data encoded in quantum states. Trainin…
Novel Approaches for ML-Assisted Particle Track Reconstruction and Hit Clustering
Uraz Odyurt, Nadezhda Dobreva, Zef Wolffs +6
Track reconstruction is a vital aspect of High-Energy Physics (HEP) and plays a critical role in major experiments. In this study, we delve into unexplored avenues for particle tra…
Digital-analog quantum convolutional neural networks for image classification
Anton Simen, Carlos Flores-Garrigos, Narendra N. Hegade +6
We propose digital-analog quantum kernels for enhancing the detection of complex features in the classification of images. We consider multipartite-entangled analog blocks, stemmin…
Dropout is all you need: robust two-qubit gate with reinforcement learning
Tian-Niu Xu, Yongcheng Ding, José D. Martín-Guerrero +1
In the realm of quantum control, reinforcement learning, a prominent branch of machine learning, emerges as a competitive candidate for computer-assisted optimal design for experim…