Calo-VQ: Vector-Quantized Two-Stage Generative Model in Calorimeter Simulation

no code implementations • 10 May 2024 • Qibin Liu, Chase Shimmin, Xiulong Liu, Eli Shlizerman, Shu Li, Shih-Chieh Hsu

We introduce a novel machine learning method developed for the fast simulation of calorimeter detector response, adapting vector-quantized variational autoencoder (VQ-VAE).

EvoMoE: An Evolutional Mixture-of-Experts Training Framework via Dense-To-Sparse Gate

2 code implementations • 29 Dec 2021 • Xiaonan Nie, Xupeng Miao, Shijie Cao, Lingxiao Ma, Qibin Liu, Jilong Xue, Youshan Miao, Yi Liu, Zhi Yang, Bin Cui

Then it diversifies the experts and continues to train the MoE with a novel Dense-to-Sparse gate (DTS-Gate).

Language Modelling Machine Translation +1