Maximizing the information learned from finite data selects a simple
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Maximizing the information learned from finite data selects a simple model

2 May 2017

Henry H. Mattingly

Mark K. Transtrum

Michael C. Abbott

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Papers citing "Maximizing the information learned from finite data selects a simple model"

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Title
Playing it safe: information constrains collective betting strategies P. Fleig V. Balasubramanian 48 0 0 18 Apr 2023
Far from Asymptopia Michael C. Abbott B. Machta 49 2 0 06 May 2022
Deep Reference Priors: What is the best way to pretrain a model? Yansong Gao Rahul Ramesh Pratik Chaudhari BDL 47 5 0 01 Feb 2022
Statistical aspects of nuclear mass models Vojtech Kejzlar L. Neufcourt W. Nazarewicz P. Reinhard 36 40 0 11 Feb 2020
Intrinsic regularization effect in Bayesian nonlinear regression scaled by observed data Satoru Tokuda Kenji Nagata M. Okada 152 1 0 05 Jan 2020
Variational Predictive Information Bottleneck Alexander A. Alemi 53 18 0 23 Oct 2019
A high-bias, low-variance introduction to Machine Learning for physicists Pankaj Mehta Marin Bukov Ching-Hao Wang A. G. Day C. Richardson Charles K. Fisher D. Schwab AI4CE 133 883 0 23 Mar 2018
A scaling law from discrete to continuous solutions of channel capacity problems in the low-noise limit Michael C. Abbott B. Machta 34 6 0 25 Oct 2017