4 citations · 5 across the 6 of their papers we have counts for
6 papers
Machine learning independent conservation laws through neural deflation
Wei Zhu, Hong-Kun Zhang, P. G. Kevrekidis
We introduce a methodology for seeking conservation laws within a Hamiltonian dynamical system, which we term ``neural deflation''. Inspired by deflation methods for steady states…
Continuous Detection, Rapidly React: Unseen Rumors Detection based on Continual Prompt-Tuning
Yuhui Zuo, Wei Zhu, Guoyong Cai
Since open social platforms allow for a large and continuous flow of unverified information, rumors can emerge unexpectedly and spread quickly. However, existing rumor detection (R…
Route Optimization via Environment-Aware Deep Network and Reinforcement Learning
Pengzhan Guo, Keli Xiao, Zeyang Ye +1
Vehicle mobility optimization in urban areas is a long-standing problem in smart city and spatial data analysis. Given the complex urban scenario and unpredictable social events, o…
Weighted Aggregating Stochastic Gradient Descent for Parallel Deep Learning
Pengzhan Guo, Zeyang Ye, Keli Xiao +1
This paper investigates the stochastic optimization problem with a focus on developing scalable parallel algorithms for deep learning tasks. Our solution involves a reformation of…
Stop memorizing: A data-dependent regularization framework for intrinsic pattern learning
Wei Zhu, Qiang Qiu, Bao Wang +3
Deep neural networks (DNNs) typically have enough capacity to fit random data by brute force even when conventional data-dependent regularizations focusing on the geometry of the f…
LDMNet: Low Dimensional Manifold Regularized Neural Networks
Wei Zhu, Qiang Qiu, Jiaji Huang +3
Deep neural networks have proved very successful on archetypal tasks for which large training sets are available, but when the training data are scarce, their performance suffers f…