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Aug 5, 2022 · The neural information theory attempts to use the assumptions of electronic communication; despite the experimental evidence that the neural ...
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This chapter discusses the role of information theory for analysis of neural networks using differential geometric ideas. Information theory is useful for ...
Information-theoretic approaches provide a novel set of tools that can expand the scope of classical approaches to causal inference and discovery problems in a ...
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May 16, 2019 · It is commonly believed that the hidden layers of deep neural networks (DNNs) attempt to extract informative features for learning tasks.
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Sep 20, 2023 · Our approach allays prominent concerns that applying information-theoretic perspectives to modeling brain and behavior requires complex encoding ...
What are the reason behind the existence of adversarial examples? In this thesis I use a formal mathematical representation of neural networks to investigate ...
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Apr 30, 2020 · In order to measure and quantify uncertainty in a mathematically rigorous way, information theory was proposed by Claude Shannon in 1948. The ...
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This book presents a new approach to modeling complex information processing in living systems. Traditional information-theoretic methods in neural networks are ...
Apr 4, 2018 · Originally, a concept of information theory. Encoder is simply compresses the information and decoder expands the encoded information. In case ...
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In this Presidential Lecture, Miles Cranmer will outline an innovative approach that leverages neural networks in the scientific process. Rather than directly ...
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