Tamas Erdelyi - Academia.edu (original) (raw)
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Papers by Tamas Erdelyi
arXiv (Cornell University), Oct 9, 2018
Proceedings of the American Mathematical Society, Apr 7, 2023
arXiv (Cornell University), Jun 23, 2012
Journal of Approximation Theory, Feb 1, 2020
Mathematika, Nov 26, 2019
Acta Mathematica Hungarica, Jun 1, 1994
arXiv (Cornell University), Feb 20, 2017
Journal of Mathematical Analysis and Applications, Dec 1, 2015
Proceedings of the American Mathematical Society, May 1, 1995
arXiv (Cornell University), Jun 20, 2012
Comptes Rendus Mathematique, Mar 1, 2008
arXiv (Cornell University), Jun 10, 2014
arXiv (Cornell University), Jun 11, 2014
arXiv (Cornell University), Sep 20, 2018
Colloquium Mathematicum, 2001
Mathematical proceedings of the Cambridge Philosophical Society, Jul 13, 2011
Analysis Mathematica, Dec 1, 2019
Fluctuation and Noise Letters, 2020
We introduce an information theoretic framework for a quantitative measure of originality to mode... more We introduce an information theoretic framework for a quantitative measure of originality to model the impact of various classes of biases, errors and error corrections on scientific research. Some of the open problems are also outlined.
arXiv (Cornell University), Oct 9, 2022
arXiv (Cornell University), Oct 9, 2018
Proceedings of the American Mathematical Society, Apr 7, 2023
arXiv (Cornell University), Jun 23, 2012
Journal of Approximation Theory, Feb 1, 2020
Mathematika, Nov 26, 2019
Acta Mathematica Hungarica, Jun 1, 1994
arXiv (Cornell University), Feb 20, 2017
Journal of Mathematical Analysis and Applications, Dec 1, 2015
Proceedings of the American Mathematical Society, May 1, 1995
arXiv (Cornell University), Jun 20, 2012
Comptes Rendus Mathematique, Mar 1, 2008
arXiv (Cornell University), Jun 10, 2014
arXiv (Cornell University), Jun 11, 2014
arXiv (Cornell University), Sep 20, 2018
Colloquium Mathematicum, 2001
Mathematical proceedings of the Cambridge Philosophical Society, Jul 13, 2011
Analysis Mathematica, Dec 1, 2019
Fluctuation and Noise Letters, 2020
We introduce an information theoretic framework for a quantitative measure of originality to mode... more We introduce an information theoretic framework for a quantitative measure of originality to model the impact of various classes of biases, errors and error corrections on scientific research. Some of the open problems are also outlined.
arXiv (Cornell University), Oct 9, 2022