Information TheoryInformation theory quantifies how much information a neural response carries about the stimulus. This can be compared to the information transferred in particular models of the stimulus-response function and to maximum possible information transfer. Such comparisons are crucial because ...
A. Borst, F. E. Theunissen. Information theory and neural coding.Nature Neuroscience, vol. 2, no. 11, pp. 947–957, 1999. DOI:https://doi.org/10.1038/14731. ArticleGoogle Scholar R. Q. Quiroga, S. Panzeri. Extracting information from neuronal populations: Information theory and decoding ...
E. Information theory and neural coding. Nature Neurosci. 2, 947– 957 (1999). Article CAS Google Scholar Usrey, W. & Reid, R. Synchronous activity in the visual system. Annu. Rev. Physiol. 61, 435– 456 (1999). Article CAS Google Scholar Zemel, R., Dayan, P. & Pouget, A. ...
coding theory and techniques, data compression, sequences, signal processing, detection and estimation, pattern recognition, learning and inference, communications and communication networks, complexity and cryptography, and quantum information theory and coding. Papers published in the IEEE Transactions on ...
1 Introduction to Information Theory 2 Probability, Entropy, and Inference 3 More about Inference Part I Data Compression 4 The Source Coding Theorem 5 Symbol Codes ··· (更多) 原文摘录 ···(全部) Probabilities can be used in two ways. 1. Probabilities can describe frequencies of outcomes...
Decoding has the advantage of being similar to real behavioural calculations, but it may lose information contained in the neural responses. Information theory considers all the information in the neural response, but it is more difficult to compute for large populations and its values may not be ...
Self-supervised learning via maximum entropy coding. Advances in Neural Information Processing Systems, 35:34091–34105, 2022. 2. Introduction Part2 翻译 然而,现有的最大熵编码框架没有明确区分来自不同增广分支的特征矩阵,阻碍了其与Alignment loss的集成。为了弥合这一差距,我们引入了矩阵信息论。通过将熵...
robotics) Social and economic aspects of machine learning (e.g., fairness, interpretability, human-AI interaction, privacy, safety, strategic behavior) Theory (e.g., control theory, learning theory, algorithmic game theory) Machine learning is a rapidly evolving field, and so we welcome interdisci...
Coding for Communication and Storage Big Data Analytics Communication Theory Coding Theory Compressed Sensing and Sparsity Complexity and Computation Theory Detection and Estimation Cryptography and Security Information Theory and Statistics Emerging Applications of Information Theory ...
Behavioral and economic theory dictate that we decide between options based on their values. However, humans and animals eagerly seek information about uncertain future rewards, even when this does not provide any objective value. This implies that decisions are made by endowing information with subje...