Publications (6)
Time Series Foundation Models for Process Model Forecasting
Yongbo Yu, Jari Peeperkorn, Johannes De Smedt +1
Process Model Forecasting (PMF) aims to predict how the control-flow structure of a process evolves over time by modeling the temporal dynamics of directly-follows (DF) relations,…
Network Embedding via Deep Prediction Model
Xin Sun, Zenghui Song, Yongbo Yu +3
Network-structured data becomes ubiquitous in daily life and is growing at a rapid pace. It presents great challenges to feature engineering due to the high non-linearity and spars…
A two-step energy injection explanation for the rebrightenings of the multi-band afterglow of GRB 081029
Yongbo Yu, Yongfeng Huang
The afterglow of GRB 081029 showed unusual behavior, with a significant rebrightening being observed at optical wavelength at about 3000 s after the burst. One possible explanation…
PRformer: Pyramidal Recurrent Transformer for Multivariate Time Series Forecasting
Yongbo Yu, Weizhong Yu, Feiping Nie +1
The self-attention mechanism in Transformer architecture, invariant to sequence order, necessitates positional embeddings to encode temporal order in time series prediction. We arg…
FedHC: A Scalable Federated Learning Framework for Heterogeneous and Resource-Constrained Clients
Min Zhang, Fuxun Yu, Yongbo Yu +3
Federated Learning (FL) is a distributed learning paradigm that empowers edge devices to collaboratively learn a global model leveraging local data. Simulating FL on GPU is essenti…
GACER: Granularity-Aware ConcurrEncy Regulation for Multi-Tenant Deep Learning
Yongbo Yu, Fuxun Yu, Mingjia Zhang +4
As deep learning continues to advance and is applied to increasingly complex scenarios, the demand for concurrent deployment of multiple neural network models has arisen. This dema…