Results 111 to 120 of about 24,126 (306)

Cogrowth of regular graphs [PDF]

Proceedings of the American Mathematical Society, 1992
Let G \mathcal {G} be a
openaire   +2 more sources

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

Advanced Energy Materials, EarlyView.
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park, Saeed Pourasad, Jinhong Mun, Arunkumar Chitteth Rajan, Tae Hyeon Park, Anand Rohit, Mohammad Zafari, Tan‐Lien Pham, Eunjae Jung, Bonseung Koo, Miran Ha, Gi Beom Sim, Hyun Gyu Park, Won Woong Choi, Kwanghyeon Jo, Soohaeng Yoo Willow, David ChangMo Yang, Chang Woo Myung, Geunsik Lee, Kwang S. Kim   +19 more
wiley   +1 more source

Consistent multi-layer subtask tracker via hyper-graph regularization

, 2017
Most multi-task learning based trackers adopt similar task definition by assuming that all tasks share a common feature set, which can't cover the real situation well.
Fan BJ(范保杰), Cong Y(丛杨)
core  

Application of Neural Networks for Advanced Ir Spectroscopy Characterization of Ceria Catalysts Surfaces

Advanced Intelligent Discovery, EarlyView.
A novel convolutional neural network architecture enables rapid, unsupervised analysis of IR spectroscopic data from DRIFTS and IRRAS. By combining synthetic data generation with parallel convolutional layers and advanced regularization, the model accurately resolves spectral features of adsorbed CO, offering real‐time insights into ceria surface ...
Mehrdad Jalali, Lachlan Caulfield, Eric Sauter, Alexei Nefedov, Chengwu Yang, Christof Wöll   +5 more
wiley   +1 more source

Measure Based Regularization

, 2003
We address in this paper the question of how the knowledge of the marginal distribution P (x) can be incorporated in a learning algorithm. We suggest three theoretical methods for taking into account this distribution for regularization and provide ...
Hein, Matthias, Bousquet, Olivier, Bousquet, O., Matthias Hein, Chapelle, O., Olivier Chapelle, Olivier Bousquet, Hein, M., Chapelle, Olivier   +8 more
core  

An Overview of Co-Clustering via Matrix Factorization

IEEE Access, 2019
Co-clustering algorithms have been widely used for text clustering and gene expression through matrix factorization. In recent years, diverse co-clustering algorithms which group data points and features synchronously have shown their advantages over ...
Renjie Lin, Shiping Wang, Wenzhong Guo
doaj   +1 more source

Accelerating Primary Screening of USP8 Inhibitors from Drug Repurposing Databases with Tree‐Based Machine Learning

Advanced Intelligent Discovery, EarlyView.
This study introduces a tree‐based machine learning approach to accelerate USP8 inhibitor discovery. The best‐performing model identified 100 high‐confidence repurposable compounds, half already approved or in clinical trials, and uncovered novel scaffolds not previously studied. These findings offer a solid foundation for rapid experimental follow‐up,
Yik Kwong Ng, Sharon Ai Er Lam, Wei Chun Lim, Hannah Hui Min Toh, Shi Jun Ang   +4 more
wiley   +1 more source

GSLDA: Supervised topic model with graph regularization

, 2014
In this work, we study the problem of regularizing supervised topic model using graph structure. Supervised topic model generates each document independently, whereas in many applications there are links among documents, which are quite useful for ...
Yan, Qiuling, Yang, Dongqing, Qiuling Yan, Dongqing Yang   +3 more
core   +1 more source

Computer Vision Pipeline for Image Analysis for Freeze‐Fracture Electron Microscopy: Rosette Cellulose Synthase Complexes Case

Advanced Intelligent Discovery, EarlyView.
This paper presents a computer vision (deep learning) pipeline integrating YOLOv8 and YOLOv9 for automated detection, segmentation, and analysis of rosette cellulose synthase complexes in freeze‐fracture electron microscopy images. The study explores curated dataset expansion for model improvement and highlights pipeline accuracy, speed ...
Siri Mudunuri, Leala Carbonneau, Eric M. Roberts, Alison W. Roberts, Candace H. Haigler, Alexey V. Gulyuk, Yaroslava G. Yingling   +6 more
wiley   +1 more source

Robust Multi-class Graph Transduction with higher order regularization

, 2015
Graph transduction refers to a family of algorithms that learn from both labeled and unlabeled examples using a weighted graph and scarce label information via regularization or label propagation.
Batista, Gustavo Enrique de Almeida Prado Alves, Sousa, Celso Andre Rodrigues de   +1 more
core   +1 more source