6 citations · 11 across the 4 of their papers we have counts for
6 papers
MemT-1.0: Towards Memory-Native Evolution
Zhiyu Li, Zeyu Zhang, Linyun Liu +71
Memory-native evolution requires making memory an intrinsic capability of foundation models, enabling them to continuously accumulate and utilize information. To this end, we intro…
An output scaling layer boosts deep neural networks for multiscale ODE systems
Yuxiao Yi, Weizong Wang, Tianhan Zhang +1
Simulating complex diffusion-reaction systems is often prohibitively expensive due to the high dimensionality and stiffness of the underlying ODEs, where state variables may span t…
Frequency-Aware Ensemble Learning for BraTS 2025 Pediatric Brain Tumor Segmentation
Yuxiao Yi, Qingyao Zhuang, Zhi-Qin John Xu +3
Pediatric brain tumor segmentation presents unique challenges due to the rarity and heterogeneity of these malignancies, yet remains critical for clinical diagnosis and treatment p…
Deep Neural Networks for Modeling Astrophysical Nuclear Reacting Flows
Xiaoyu Zhang, Yuxiao Yi, Lile Wang +3
In astrophysical simulations, nuclear reacting flows pose computational challenges due to the stiffness of reaction networks. We introduce neural network-based surrogate models usi…
Solving multiscale dynamical systems by deep learning
Junjie Yao, Yuxiao Yi, Liangkai Hang +5
Multiscale dynamical systems, modeled by high-dimensional stiff ordinary differential equations (ODEs) with wide-ranging characteristic timescales, arise across diverse fields of s…
A multi-scale sampling method for accurate and robust deep neural network to predict combustion chemical kinetics
Tianhan Zhang, Yuxiao Yi, Yifan Xu +4
Machine learning has long been considered as a black box for predicting combustion chemical kinetics due to the extremely large number of parameters and the lack of evaluation stan…