Results 61 to 70 of about 26,557 (311)

Prototypical Graph Contrastive Learning [PDF]

, 2022
Graph-level representations are critical in various real-world applications, such as predicting the properties of molecules. But in practice, precise graph annotations are generally very expensive and time-consuming.
Zhao, Ruihui, Eric Xing, Chen Liu, Xing, Eric, Zhou, Pan, Shuojia Wang, LIU, Chen, Hu, Zi-Yuan, Pan Zhou, Wang, Shuojia, Zheng, Yefeng, Lin, Shuai, Xiaodan Liang, Lin, Liang, Zi-Yuan Hu, Ruihui Zhao, Yefeng Zheng, Liang Lin, Shuai Lin, Liang, Xiaodan   +19 more
core   +2 more sources

Contrastive Mask Learning for Self-Supervised 3D Skeleton-Based Action Recognition

Sensors
In this paper, we propose a contrastive mask learning (CML) method for self-supervised 3D skeleton-based action recognition. Specifically, the mask modeling mechanism is integrated into multi-level contrastive learning with the aim of forming a mutually ...
Haoyuan Zhang
doaj   +1 more source

Gut microbiome and aging—A dynamic interplay of microbes, metabolites, and the immune system

FEBS Letters, EarlyView.
Age‐dependent shifts in microbial communities engender shifts in microbial metabolite profiles. These in turn drive shifts in barrier surface permeability of the gut and brain and induce immune activation. When paired with preexisting age‐related chronic inflammation this increases the risk of neuroinflammation and neurodegenerative diseases.
Aaron Mehl, Eran Blacher
wiley   +1 more source

Learning in Markov Random Fields with Contrastive Free Energies [PDF]

, 2005
Learning Markov random field (MRF) models is notoriously hard due to the presence of a global normalization factor. In this paper we present a new framework for learning MRF models based on the contrastive free energy (CF) objective function.
Welling, Max, Sutton, Charles, Max Welling, Charles Sutton   +3 more
core  

Contrastive Learning for Object Detection

CoRR, 2022
arXiv admin note: substantial text overlap with arXiv:2208 ...
Rishab Balasubramanian, Kunal Rathore
openaire   +2 more sources

The human gut microbiome across the life course

FEBS Letters, EarlyView.
Despite significant individual variation and continuous change throughout life, the human gut microbiome follows some life stage‐specific trends. This article provides a brief overview of how gut microbiome composition shifts across different phases of life. Created in BioRender. Özkurt, E. (2026) https://BioRender.com/8q4nrnc.
Alise J. Ponsero, Basak Bahcivanci, Antonietta Hayhoe, Animesh Acharjee, Ezgi Özkurt   +4 more
wiley   +1 more source

XSimGCL: Towards Extremely Simple Graph Contrastive Learning for Recommendation [PDF]

, 2023
Contrastive learning (CL) has recently been demonstrated critical in improving recommendation performance. The underlying principle of CL-based recommendation models is to ensure the consistency between representations derived from different graph ...
Tong Chen, Xin Xia, Nguyen Quoc Viet Hung, Cui, L, Junliang Yu, Lizhen Cui, Yu, J, Chen, T, Xia, X, Hongzhi Yin, Hung, NQV, Yin, H   +11 more
core   +1 more source

Study on Graph Collaborative Filtering Model Based on FeatureNet Contrastive Learning [PDF]

Jisuanji kexue
Graph-based collaborative filtering recommendation techniques have gained significant attention for their ability to efficiently process large-scale interaction data.However,the effectiveness of these techniques is limited by the sparsity of data in real-
WU Pengyuan, FANG Wei
doaj   +1 more source

Tuned Contrastive Learning

2025 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
In recent times, contrastive learning based loss functions have become increasingly popular for visual self-supervised representation learning owing to their state-of-the-art (SOTA) performance. Most of the modern contrastive learning methods generalize only to one positive and multiple negatives per anchor.
Chaitanya Animesh, Manmohan Chandraker
openaire   +2 more sources

Policy Contrastive Imitation Learning

CoRR, 2023
Adversarial imitation learning (AIL) is a popular method that has recently achieved much success. However, the performance of AIL is still unsatisfactory on the more challenging tasks. We find that one of the major reasons is due to the low quality of AIL discriminator representation.
Jialei Huang, Zhao-Heng Yin, Yingdong Hu, Yang Gao 0029   +3 more
openaire   +3 more sources