11 citations · 31 across the 13 of their papers we have counts for
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cs.AI2024★ 1 cited
Efficient Compression of Sparse Accelerator Data Using Implicit Neural Representations and Importance Sampling
Xihaier Luo, Samuel Lurvey, Yi Huang +3
High-energy, large-scale particle colliders in nuclear and high-energy physics generate data at extraordinary rates, reaching up to terabyte and several petabytes per second, r…
physics.ins-det2024
Variable Rate Neural Compression for Sparse Detector Data
Yi Huang, Yeonju Go, Jin Huang +9
High-energy large-scale particle colliders generate data at extraordinary rates. Developing real-time high-throughput data compression algorithms to reduce data volume and meet the…
physics.data-an2024★ 7 cited
Effectiveness of denoising diffusion probabilistic models for fast and high-fidelity whole-event simulation in high-energy heavy-ion experiments
Yeonju Go, Dmitrii Torbunov, Timothy Rinn +6
Artificial intelligence (AI) generative models, such as generative adversarial networks (GANs), variational auto-encoders, and normalizing flows, have been widely used and studied…