Results 261 to 270 of about 447,603 (295)

When Dimensionality Reduction Meets Graph (Drawing) Theory: Introducing a Common Framework, Challenges and Opportunities

arXiv.org
In the vast landscape of visualization research, Dimensionality Reduction (DR) and graph analysis are two popular subfields, often essential to most visual data analytics setups.
F. Paulovich, A. Arleo, S. V. D. Elzen
semanticscholar   +1 more source

Exploring Automata Theory with an Educational Activity Using Graph Grammar for K-12 Education

Anais do XXXV Simpósio Brasileiro de Informática na Educação (SBIE 2024)
This paper proposes an educational activity for K-12 Education, aligned with the Brazilian National Common Curricular Base, which explores Automata Theory using Graph Grammar.
Júlia Varanda da Silva, Braz Araujo da Silva Junior, S. A. C. Cavalheiro, Luciana Foss   +3 more
semanticscholar   +1 more source

Learn Beneficial Noise as Graph Augmentation

International Conference on Machine Learning
Although graph contrastive learning (GCL) has been widely investigated, it is still a challenge to generate effective and stable graph augmentations.
Siqi Huang, Yanchen Xu, Hongyuan Zhang, Xuelong Li   +3 more
semanticscholar   +1 more source

Uncertainty-Aware Graph Neural Networks: A Multihop Evidence Fusion Approach

IEEE Transactions on Neural Networks and Learning Systems
Graph neural networks (GNNs) excel in graph representation learning by integrating graph structure and node features. Existing GNNs, unfortunately, fail to account for the uncertainty of class probabilities that vary with the depth of the model, leading ...
Qingfeng Chen, Shiyuan Li, Yixin Liu, Shirui Pan, Geoffrey I. Webb, Shichao Zhang   +5 more
semanticscholar   +1 more source

An Interactive Tool for Randomized Autogradable Graph Assessments

Technical Symposium on Computer Science Education
Mastering algorithms and graph theory requires students to understand both the theoretical concepts and the practical mechanics. While most current assessments focus on the practical aspects, a deeper understanding of the theoretical concepts is often ...
Eldar Hasanov, Dev Ahluwalia, D. Garcia, Narges Norouzi, Armando Fox   +4 more
semanticscholar   +1 more source

Teaching Practice Evaluation of Medical Mathematical Statistics Based on Knowledge Graph

2025 5th International Conference on Artificial Intelligence and Education (ICAIE)
Medical mathematical statistics is a core course in the field of medicine and pharmacy, playing a crucial role in cultivating students' professional literacy.
Di Wu, Sheng Hu, Lingzhi Hu, Junhua Hu, Hui Zhi, Xiangwen Li, Xuan Yang   +6 more
semanticscholar   +1 more source

Uncertainty in Graph Neural Networks: A Survey

Trans. Mach. Learn. Res.
Graph Neural Networks (GNNs) have been extensively used in various real-world applications. However, the predictive uncertainty of GNNs stemming from diverse sources such as inherent randomness in data and model training errors can lead to unstable and ...
Fangxin Wang, Yuqing Liu, Kay Liu, Yibo Wang, Sourav Medya, Philip S. Yu   +5 more
semanticscholar   +1 more source

Graph Theory: Part 1

Combinatorics, 2019
P. Mladenovic
semanticscholar   +1 more source

Poly(ADP-Ribose) polymerase (PARP) inhibitors: Exploiting a synthetic lethal strategy in the clinic

Ca-A Cancer Journal for Clinicians, 2011
Timothy A Yap, Johann Sebastian de Bono
exaly  

Computational predictions of energy materials using density functional theory

Nature Reviews Materials, 2016
Anubhav Jain, Yongwoo Shin, Kristin A Persson   +2 more
exaly