Results 131 to 140 of about 601,753 (327)
AIChE Journal, EarlyView.Abstract In this study, various adsorption models using neural networks were developed and integrated into a mechanistic chromatography transport model, resulting in hybrid models. A systematic screening of 10 different hybrid model structures was performed to find the optimal balance between mechanistic and data‐driven components in modeling ...
Jesper Frandsen +6 more
wiley +1 more source
Semi-supervised Learning from Unbalanced Labeled Data – An Improvement [PDF]
, 2004 Te Ming Huang, Vojislav Kecman
openalex +1 more source
Semi-supervised Sequence Learning
, 2015 We present two approaches that use unlabeled data to improve sequence learning with recurrent networks. The first approach is to predict what comes next in a sequence, which is a conventional language model in natural language processing. The second approach is to use a sequence autoencoder, which reads the input sequence into a vector and predicts the
Dai, Andrew M., Le, Quoc V.
openaire +2 more sources
Inverse Engineering of Mg Alloys Using Guided Oversampling and Semi‐Supervised Learning
Advanced Intelligent Discovery, EarlyView.End‐to‐end design of engineering materials such as Mg alloys must include the properties, structure, and post‐synthesis processing methods. However, this is challenging when destructive mechanical testing is needed to annotate unseen data, and the processing methods for hypothetical alloys are unknown.
Amanda S. Barnard
wiley +1 more source
Advanced Intelligent Discovery, EarlyView.This study applies QSAR‐based new approach methodologies to 90 synthetic tattoo and permanent makeup pigments, revealing systemic links between their physicochemical properties and absorption, distribution, metabolism, and elimination profiles. The correlation‐driven analysis using SwissADME, ChemBCPP, and principal component analysis uncovers insights
Girija Bansod +10 more
wiley +1 more source
Semi-supervised learning techniques: k-means clustering in OODB fragmentation [PDF]
, 2005 Adrian Sergiu Dărăbant, A. Campan
openalex +1 more source
Interpolation Consistency Training for Semi-Supervised Learning [PDF]
International Joint Conference on Artificial Intelligence, 2019 Vikas Verma +4 more
semanticscholar +1 more source
Advanced Intelligent Discovery, EarlyView.Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley +1 more source
Joint Situational Assessment‐Hierarchical Decision‐Making Framework for Maneuver Intent Decisions
Advanced Intelligent Systems, EarlyView.This study introduces a new framework for decision‐making in unmanned combat aerial vehicles (UCAVs), integrating graph convolutional networks and hierarchical reinforcement learning (HRL). The method tackles adopts a curriculum‐based training approach guided by cross‐entropy rewards.
Ruihai Chen +4 more
wiley +1 more source