Results 261 to 270 of about 36,403 (314)

Enhancing generalized spectral clustering with embedding Laplacian graph regularization

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract An enhanced generalised spectral clustering framework that addresses the limitations of existing methods by incorporating the Laplacian graph and group effect into a regularisation term is presented. By doing so, the framework significantly enhances discrimination power and proves highly effective in handling noisy data.
Hengmin Zhang, Jian Yang, Bob Zhang, Yang Tang, Wenli Du, Bihan Wen   +5 more
wiley   +1 more source

Assessing U.S. public perceptions of global warming using social survey and climate data. [PDF]

MethodsX
Wei X, Bohnett E, An L.
europepmc   +1 more source

Graph neural link predictor based on cycle structure

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract Currently, the link prediction algorithms primarily focus on studying the interaction between nodes based on chain structure and star structure, which predominantly rely on low‐order structural information and do not explore the multivariate interactions between nodes from the perspective of higher‐order structural information present in the ...
Yanlin Yang, Zhonglin Ye, Lei Meng, Mingyuan Li, Haixing Zhao   +4 more
wiley   +1 more source

The fly connectome reveals a path to the effectome. [PDF]

Nature
Pospisil DA, Aragon MJ, Dorkenwald S, Matsliah A, Sterling AR, Schlegel P, Yu SC, McKellar CE, Costa M, Eichler K, Jefferis GSXE, Murthy M, Pillow JW.   +12 more
europepmc   +1 more source

Speaker independent speech recognition based on neural networks of each category with embedded eigenvectors

, 1990
Yasuyuki Masai, H. Matsuura, Tsuneo Nitta   +2 more
openalex   +2 more sources

Laplacian attention: A plug‐and‐play algorithm without increasing model complexity for vision tasks

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract Most prevailing attention mechanism modules in contemporary research are convolution‐based modules, and while these modules contribute to enhancing the accuracy of deep learning networks in visual tasks, they concurrently augment the overall model complexity.
Xiaolei Chen, Yubing Lu, Runyu Wen
wiley   +1 more source

The origin of sound damping in amorphous solids: Defects and beyond. [PDF]

Sci Adv
Flenner E, Szamel G.
europepmc   +1 more source

Advancing skin cancer detection integrating a novel unsupervised classification and enhanced imaging techniques

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract Skin cancer, a severe health threat, can spread rapidly if undetected. Therefore, early detection can lead to an advanced and efficient diagnosis, thus reducing mortality. Unsupervised classification techniques analyse extensive skin image datasets, identifying patterns and anomalies without prior labelling, facilitating early detection and ...
Md. Abdur Rahman, Nur Mohammad Fahad, Mohaimenul Azam Khan Raiaan, Mirjam Jonkman, Friso De Boer, Sami Azam   +5 more
wiley   +1 more source

Single unit-derived connectivity networks in tuberous sclerosis complex reveal propensity for network hypersynchrony driven by tuber-tuber interactions. [PDF]

Sci Rep
Chari A, Hernan AE, Mahoney JM, Thornton R, Tahir MZ, Tisdall MM, Scott RC.   +6 more
europepmc   +1 more source

Molecular Retrosynthesis Top‐K Prediction Based on the Latent Generation Process

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT In the field of organic synthesis, the core objective of retrosynthetic methods is to deduce possible synthetic routes and precursor molecules for complex target molecules. Traditional retrosynthetic methods, such as template‐based retrosynthesis, have high accuracy and interpretability in specific types of reactions but are limited by the ...
Yupeng Liu, Han Zhang, Rui Hu
wiley   +1 more source