Results 11 to 20 of about 2,204,167 (303)
Diffusion-Based Causal Representation Learning
EntropyCausal reasoning can be considered a cornerstone of intelligent systems. Having access to an underlying causal graph comes with the promise of cause–effect estimation and the identification of efficient and safe interventions.
Amir Mohammad Karimi Mamaghan +4 more
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Distributed Variational Representation Learning [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021 The problem of distributed representation learning is one in which multiple sources of information X1,…, XK are processed separately so as to learn as much information as possible about some ground truth Y. We investigate this problem from information-theoretic grounds, through a generalization of Tishby's centralized Information Bottleneck (IB) method
Aguerri, Inaki Estella +1 more
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Toward Causal Representation Learning [PDF]
Proceedings of the IEEE, 2021 ISSN:1558 ...
Bernhard Scholkopf +6 more
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Learning Overcomplete Representations [PDF]
Neural Computation, 2000 In an overcomplete basis, the number of basis vectors is greater than the dimensionality of the input, and the representation of an input is not a unique combination of basis vectors. Overcomplete representations have been advocated because they have greater robustness in the presence of noise, can be sparser, and can have greater flexibility in ...
M S, Lewicki, T J, Sejnowski
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Molecular set representation learning
Nature Machine Intelligence, 2023 Computational representation of molecules can take many forms, including graphs, string-encodings of graphs, binary vectors, or learned embeddings in the form of real-valued vectors. These representations are then used in downstream classification and regression tasks using a wide range of machine-learning models.
Maria Boulougouri +2 more
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Relation-Guided Representation Learning [PDF]
Neural Networks, 2020 Appear in Neural ...
Zhao Kang +4 more
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Learning representations from dendrograms [PDF]
Machine Learning, 2020 AbstractWe propose unsupervised representation learning and feature extraction from dendrograms. The commonly used Minimax distance measures correspond to building a dendrogram with single linkage criterion, with defining specific forms of a level function and a distance function over that. Therefore, we extend this method to arbitrary dendrograms.
Morteza Haghir Chehreghani +1 more
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IEEE Access, 2021 Machine learning has been widely applied in the fields of biomedicine, computational biology, bioinformatics, image processing, and so on. The performance of machine learning methods mainly relies on feature representation that is the mapping from ...
Feifei Cui +5 more
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Involvement of NRF2 in Breast Cancer and Possible Therapeutical Role of Polyphenols and Melatonin
Molecules, 2021 Oxidative stress is defined as a disturbance in the prooxidant/antioxidant balance in favor of the former and a loss of control over redox signaling processes, leading to potential biomolecular damage.
Alev Tascioglu Aliyev +4 more
doaj +1 more source
Journal of Medives: Journal of Mathematics Education IKIP Veteran Semarang, 2022 This research is a descriptive study that aims to explain students' mathematical representation abilities in solving AKM numeracy questions after problem based learning is implemented, to explain the implementation of the problem based learning learning ...
Karenina Rizka Alifa +3 more
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