A deep learning approach for solving Poisson's equations
Partial differential equations (PDEs) have a lot of applications in different fields of research
during the last decades. In this paper, we study a mesh-free deep learning method for …
during the last decades. In this paper, we study a mesh-free deep learning method for …
From oracle generalization bound toward empirical inequality
MA Hajiani, B Seyfe - Information Sciences, 2023 - Elsevier
Learning guarantees are tools for analyzing the performance of statistical learning problems.
Most of the existing guarantees are oracle generalization bounds and are proper for …
Most of the existing guarantees are oracle generalization bounds and are proper for …
Sequential Importance Sampling for Hybrid Model Bayesian Inference to Support Bioprocess Mechanism Learning and Robust Control
Driven by the critical needs of biomanufacturing 4.0, we introduce a probabilistic knowledge
graph hybrid model characterizing the risk-and science-based understanding of bioprocess …
graph hybrid model characterizing the risk-and science-based understanding of bioprocess …
[PDF][PDF] B. Feng, G. Pedrielli, Y. Peng, S. Shashaani, E. Song, CG Corlu, LH Lee, P. Lendermann, eds.
W Xie, K Wang, H Zheng - coe.neu.edu
Driven by the critical needs of biomanufacturing 4.0, we present a probabilistic knowledge
graph hybrid model characterizing complex spatial-temporal causal interdependencies of …
graph hybrid model characterizing complex spatial-temporal causal interdependencies of …