4 papers · 1 filter
Elliptic Loss Regularization
Ali Hasan, Haoming Yang, Yuting Ng +1
Regularizing neural networks is important for anticipating model behavior in regions of the data space that are not well represented. In this work, we propose a regularization tech…
Parabolic Continual Learning
Haoming Yang, Ali Hasan, Vahid Tarokh
Regularizing continual learning techniques is important for anticipating algorithmic behavior under new realizations of data. We introduce a new approach to continual learning by i…
S2TX: Cross-Attention Multi-Scale State-Space Transformer for Time Series Forecasting
Zihao Wu, Juncheng Dong, Haoming Yang +1
Time series forecasting has recently achieved significant progress with multi-scale models to address the heterogeneity between long and short range patterns. Despite their state-o…
Neural McKean-Vlasov Processes: Distributional Dependence in Diffusion Processes
Haoming Yang, Ali Hasan, Yuting Ng +1
McKean-Vlasov stochastic differential equations (MV-SDEs) provide a mathematical description of the behavior of an infinite number of interacting particles by imposing a dependence…