117 citations · 207 across the 12 of their papers we have counts for
9 papers · 1 filter
Feature Space Singularity for Out-of-Distribution Detection
Haiwen Huang, Zhihan Li, Lulu Wang +3
Out-of-Distribution (OoD) detection is important for building safe artificial intelligence systems. However, current OoD detection methods still cannot meet the performance require…
Deep Interactive Denoiser (DID) for X-Ray Computed Tomography
Ti Bai, Biling Wang, Dan Nguyen +5
Low dose computed tomography (LDCT) is desirable for both diagnostic imaging and image guided interventions. Denoisers are openly used to improve the quality of LDCT. Deep learning…
Meta-MgNet: Meta Multigrid Networks for Solving Parameterized Partial Differential Equations
Yuyan Chen, Bin Dong, Jinchao Xu
This paper studies numerical solutions for parameterized partial differential equations (P-PDEs) with deep learning (DL). P-PDEs arise in many important application areas and the c…
A Practical Layer-Parallel Training Algorithm for Residual Networks
Qi Sun, Hexin Dong, Zewei Chen +5
Gradient-based algorithms for training ResNets typically require a forward pass of the input data, followed by back-propagating the objective gradient to update parameters, which a…
Transferred Discrepancy: Quantifying the Difference Between Representations
Yunzhen Feng, Runtian Zhai, Di He +2
Understanding what information neural networks capture is an essential problem in deep learning, and studying whether different models capture similar features is an initial step t…
RODE-Net: Learning Ordinary Differential Equations with Randomness from Data
Junyu Liu, Zichao Long, Ranran Wang +2
Random ordinary differential equations (RODEs), i.e. ODEs with random parameters, are often used to model complex dynamics. Most existing methods to identify unknown governing RODE…