An Enquiry on similarities between Renormalization Group and Auto-Encoders using Transfer Learning Article Swipe
Mohak Shukla
,
Ajay D. Thakur
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2108.06157
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2108.06157
Physicists have had a keen interest in the areas of Artificial Intelligence (AI) and Machine Learning (ML) for some time now, with a special inclination towards unravelling the mechanism at the core of the process of learning. In particular, exploring the underlying mathematical structure of a neural net (NN) is expected to not only help us in understanding the epistemological meaning of `Learning' but also has the potential to unravel the secrets behind the workings of the brain. Here, it is worthwhile to establish correspondences and draw parallels between methods developed in core areas of Physics and the techniques developed at the forefront of AI and ML. Although recent explorations indicating a mapping between the Renormalisation Group(RG) and Deep Learning(DL) have shown valuable insights, we intend to investigate the relationship between RG and Autoencoders(AE) in particular. We will use Transfer Learning(TL) to embed the procedure of coarse-graining in a NN and compare it with the underlying mechanism of encoding-decoding through a series of tests.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2108.06157
- https://arxiv.org/pdf/2108.06157
- OA Status
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- Related Works
- 10
- OpenAlex ID
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https://openalex.org/W4287025483Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2108.06157Digital Object Identifier
- Title
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An Enquiry on similarities between Renormalization Group and Auto-Encoders using Transfer LearningWork title
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preprintOpenAlex work type
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enPrimary language
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2021Year of publication
- Publication date
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2021-08-13Full publication date if available
- Authors
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Mohak Shukla, Ajay D. ThakurList of authors in order
- Landing page
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https://arxiv.org/abs/2108.06157Publisher landing page
- PDF URL
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https://arxiv.org/pdf/2108.06157Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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greenOpen access status per OpenAlex
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https://arxiv.org/pdf/2108.06157Direct OA link when available
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Artificial intelligence, Parallels, Mechanism (biology), Transfer of learning, Computer science, Core (optical fiber), Cognitive science, Meaning (existential), Artificial neural network, Psychology, Epistemology, Philosophy, Engineering, Telecommunications, Mechanical engineeringTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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