Estimating the effective dimension of large biological datasets using Fisher separability analysis

18 January 2019

Papers citing "Estimating the effective dimension of large biological datasets using Fisher separability analysis"

9 / 9 papers shown

Title
Geometric Signatures of Compositionality Across a Language Model's Lifetime Jin Hwa Lee Thomas Jiralerspong Lei Yu Yoshua Bengio Emily Cheng CoGe 87 1 0 02 Oct 2024
Bridging Information-Theoretic and Geometric Compression in Language Models Emily Cheng Corentin Kervadec Marco Baroni 36 17 0 20 Oct 2023
Byte Pair Encoding for Symbolic Music Nathan Fradet Nicolas Gutowski F. Chhel Jean-Pierre Briot 34 16 0 27 Jan 2023
LIDL: Local Intrinsic Dimension Estimation Using Approximate Likelihood Piotr Tempczyk Rafał Michaluk Łukasz Garncarek Przemysław Spurek Jacek Tabor Adam Goliñski 35 26 0 29 Jun 2022
Quasi-orthogonality and intrinsic dimensions as measures of learning and generalisation Qinghua Zhou Alexander N. Gorban Evgeny M. Mirkes Jonathan Bac A. Zinovyev I. Tyukin 28 2 0 30 Mar 2022
Trajectories, bifurcations and pseudotime in large clinical datasets: applications to myocardial infarction and diabetes data S. E. Golovenkin Jonathan Bac A. Chervov Evgeny M. Mirkes Y. Orlova E. Barillot A. Gorban A. Zinovyev 16 42 0 07 Jul 2020
Blessing of dimensionality at the edge I. Tyukin Alexander N. Gorban A. McEwan Sepehr Meshkinfamfard Lixin Tang 21 8 0 30 Sep 2019
Local angles and dimension estimation from data on manifolds Mateo Díaz A. Quiroz Mauricio Velasco 22 10 0 04 May 2018
Robust And Scalable Learning Of Complex Dataset Topologies Via Elpigraph L. Albergante Evgeny M. Mirkes Huidong Chen Alexis Martin Louis Faure E. Barillot Luca Pinello Alexander N. Gorban A. Zinovyev 14 56 0 20 Apr 2018