Results 201 to 210 of about 115,093 (312)

Divgcl: A Graph Contrastive Learning Model for Diverse Recommendation

Wenwen Gong, Hepeng Wang, Shuchen Li
openalex   +1 more source

Contrastive Graph Representation Learning with Adversarial Cross-view Reconstruction and Information Bottleneck [PDF]

Yuntao Shou, Haozhi Lan, Xiangyong Cao
openalex   +1 more source

Smart, Bio‐Inspired Polymers and Bio‐Based Molecules Modified by Zwitterionic Motifs to Design Next‐Generation Materials for Medical Applications

Advanced Functional Materials, EarlyView.
Bio‐based and (semi‐)synthetic zwitterion‐modified novel materials and fully synthetic next‐generation alternatives show the importance of material design for different biomedical applications. The zwitterionic character affects the physiochemical behavior of the material and deepens the understanding of chemical interaction mechanisms within the ...
Theresa M. Lutz, Jonas De Breuck, Sahar Salehi, Meike N. Leiske   +3 more
wiley   +1 more source

Dual denoising contrastive learning with multi-interest fusion for sequential recommendation. [PDF]

Sci Rep
Long H, Lu J, Dai C.
europepmc   +1 more source

Functional Materials for Environmental Energy Harvesting in Smart Agriculture via Triboelectric Nanogenerators

Advanced Functional Materials, EarlyView.
This review explores functional and responsive materials for triboelectric nanogenerators (TENGs) in sustainable smart agriculture. It examines how particulate contamination and dirt affect charge transfer and efficiency. Environmental challenges and strategies to enhance durability and responsiveness are outlined, including active functional layers ...
Rafael R. A. Silva, Giulio Fatti, Emanuel Carlos, Guilherme Ferreira, Sumita Goswami, Suman Nandy, Luiz H. C. Mattoso, Elvira Fortunato, Caio G. Otoni, Rodrigo Martins   +9 more
wiley   +1 more source

Contrastive learning enhances fairness in pathology artificial intelligence systems. [PDF]

Cell Rep Med
Lin SY, Tsai PC, Su FY, Chen CY, Li F, Zhao J, Ho YY, Lee TM, Healey E, Lin PJ, Kao TW, Vremenko D, Roetzer-Pejrimovsky T, Sholl L, Dillon D, Lin NU, Meredith D, Ligon KL, Lo YC, Chaisuriya N, Cook DJ, Woehrer A, Meyerhardt J, Ogino S, Nasrallah MP, Golden JA, Signoretti S, Chiang JH, Yu KH.   +28 more
europepmc   +1 more source

Encoder Augmentation for Multi-Task Graph Contrastive Learning

Xiaoyu Wang, Qiqi Zhang, Gen Liu, Zhongying Zhao, Hongzhi Cui   +4 more
openalex   +1 more source

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source

Contrastive learning for cell division detection and tracking in live cell imaging data. [PDF]

BMC Bioinformatics
Zyss D, Sharma A, A Ribeiro S, E Repellin C, Lai O, J C Ludlam M, Walter T, Fehri A.   +7 more
europepmc   +1 more source

Complex Cryptographic and User‐Centric Physically Unclonable Functions Enabled by Strain‐Sensitive Nanocrystals via Selective Ligand Exchange

Advanced Functional Materials, EarlyView.
This study investigates electromechanical PUFs that improve on traditional electric PUFs. The electron transport materials are coated randomly through selective ligand exchange. It produces multiple keys and a key with motion dependent on percolation and strain, and approaches almost ideal inter‐ and intra‐hamming distances.
Seungshin Lim, Hanseok Seo, Taesung Park, Byung Ku Jung, Junhyeok Park, Young Kyun Choi, Dae Yang Oh, Soong Ju Oh   +7 more
wiley   +1 more source