Contrastive representation learning of inorganic materials to overcome lack of training datasets.
Sign Up to like & getrecommendations! Published in 2022 at "Chemical communications"
DOI: 10.1039/d2cc01764d
Abstract: Data representation forms a feature space where forms data distribution that is one of the key factors determining the prediction accuracy of machine learning (ML). In particular, the data representation is crucial to handle small… read more here.
Keywords: training datasets; contrastive representation; learning inorganic; representation learning ... See more keywords
PARCEL: Physics-based Unsupervised Contrastive Representation Learning for Multi-coil MR Imaging.
Sign Up to like & getrecommendations! Published in 2022 at "IEEE/ACM transactions on computational biology and bioinformatics"
DOI: 10.1109/tcbb.2022.3213669
Abstract: With the successful application of deep learning to magnetic resonance (MR) imaging, parallel imaging techniques based on neural networks have attracted wide attention. However, in the absence of high-quality, fully sampled datasets for training, the… read more here.
Keywords: contrastive representation; physics; representation learning; unsupervised contrastive ... See more keywords
Action-driven contrastive representation for reinforcement learning
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DOI: 10.1371/journal.pone.0265456
Abstract: In reinforcement learning, reward-driven feature learning directly from high-dimensional images faces two challenges: sample-efficiency for solving control tasks and generalization to unseen observations. In prior works, these issues have been addressed through learning representation from… read more here.
Keywords: contrastive representation; reinforcement learning; action; representation ... See more keywords
Multibranch convolutional neural network with contrastive representation learning for decoding same limb motor imagery tasks
Sign Up to like & getrecommendations! Published in 2022 at "Frontiers in Human Neuroscience"
DOI: 10.3389/fnhum.2022.1032724
Abstract: Introduction Emerging deep learning approaches to decode motor imagery (MI) tasks have significantly boosted the performance of brain-computer interfaces. Although recent studies have produced satisfactory results in decoding MI tasks of different body parts, the… read more here.
Keywords: neural network; contrastive representation; representation learning; convolutional neural ... See more keywords