Improving Robustness and Uncertainty Modelling in Neural Ordinary Differential Equations

23 December 2021

Papers citing "Improving Robustness and Uncertainty Modelling in Neural Ordinary Differential Equations"

8 / 8 papers shown

Title
Understanding and Mitigating Membership Inference Risks of Neural Ordinary Differential Equations Sanghyun Hong Fan Wu A. Gruber Kookjin Lee 52 0 0 12 Jan 2025
Enhancing Low-Order Discontinuous Galerkin Methods with Neural Ordinary Differential Equations for Compressible Navier--Stokes Equations Shinhoo Kang Emil M. Constantinescu AI4CE 27 0 0 29 Oct 2023
Uncertainty and Structure in Neural Ordinary Differential Equations Katharina Ott Michael Tiemann Philipp Hennig AI4CE 31 5 0 22 May 2023
Learning Subgrid-scale Models with Neural Ordinary Differential Equations Shinhoo Kang Emil M. Constantinescu AI4CE 26 6 0 20 Dec 2022
Deep Learning Aided Laplace Based Bayesian Inference for Epidemiological Systems Wai Meng Kwok S. Dass G. Streftaris 40 3 0 17 Oct 2022
Zero Stability Well Predicts Performance of Convolutional Neural Networks Liangming Chen Long Jin Mingsheng Shang MLT 24 8 0 27 Jun 2022
TO-FLOW: Efficient Continuous Normalizing Flows with Temporal Optimization adjoint with Moving Speed Shian Du Yihong Luo Wei Chen Jian Xu Delu Zeng 37 7 0 19 Mar 2022
Latent Time Neural Ordinary Differential Equations Srinivas Anumasa P. K. Srijith BDL 24 5 0 23 Dec 2021