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Residual Dynamic Mode Decomposition Rigorous data-driven computation…
www.damtp.cam.ac.uk/user/mjc249/talks/mpEDMD_portland_mjc.pdf15 Jul 2023: with any DMD-type method! 19/19. Summary. Read more about these breakthroughs in SIAM News! ... Read more about these breakthroughs in SIAM News! Short video summariesavailable on YouTube:. -
S-D NLEVPs
www.damtp.cam.ac.uk/user/mjc249/talks/strathclyde_2023_NEP_mjc.pdf15 Jul 2023: e2107151119. [2] Antun, V., M. J. Colbrook, and A. C. Hansen. "Proving existence is not enough: Mathematical paradoxes unravel the limits of neural networks in artificial intelligence." SIAM News 55.4 ... References. , V., M. J. Colbrook, and A. C. Hansen -
Residual Dynamic Mode Decomposition Rigorous data-driven computation…
www.damtp.cam.ac.uk/user/mjc249/talks/INI_ResDMD.pdf9 Mar 2023: J. Numer. Anal., 2019.• Horning, Townsend, “FEAST for Differential Eigenvalue Problems,” SIAM J. ... Code: https://github.com/MColbrook/Residual-Dynamic-Mode-Decomposition. 34/34. Rigorous data-driven Koopmanism! Read more about these breakthroughs -
10th_Popov_Prize
www.damtp.cam.ac.uk/user/mjc249/talks/Popov_talk_FoCM_mjc.pdf15 Jul 2023: Not Enough: : Mathematical Paradoxes Unravel the Limits of Neural Networks in Artificial Intelligence,” SIAM News, May 2022.• Choi, “Some AI Systems May Be Impossible to Compute,” IEEE Spectrum, March 2022. ... 2] Antun, V., M. J. Colbrook, and A. -
A programme for computational analysis in the age of data
www.damtp.cam.ac.uk/user/mjc249/talks/SCI_talk_JMM.pdf6 Jan 2023: Spectral measures of self-adjoint operators. • C., Horning, Townsend “Computing spectral measures of self-adjoint operators,” SIAM Rev., 2021. • ... Not Enough: : Mathematical Paradoxes Unravel the Limits of Neural Networks in Artificial -
ON THE EXISTENCE OF OPTIMAL MULTI-VALUED DECODERS AND THEIR ...
www.damtp.cam.ac.uk/research/afha/anders/Version0.pdf28 Nov 2023: ON THE EXISTENCE OF OPTIMAL MULTI-VALUED DECODERS AND THEIR ACCURACYBOUNDS FOR UNDERSAMPLED INVERSE PROBLEMS. NINA M. GOTTSCHLING, PAOLO CAMPODONICO, VEGARD ANTUN, AND ANDERS C. HANSEN. ABSTRACT. Undersampled inverse problems occur everywhere in the -
WHEN CAN YOU TRUST FEATURE SELECTION? – II: ON ...
www.damtp.cam.ac.uk/research/afha/anders/InitialSubmitFeatureSelectionProbabilistic.pdf18 Dec 2023: WHEN CAN YOU TRUST FEATURE SELECTION? – II: ON THE EFFECTS OF RANDOMDATA ON CONDITION IN STATISTICS AND OPTIMISATION. ALEXANDER BASTOUNIS, FELIPE CUCKER, AND ANDERS C. HANSEN. ABSTRACT. In Part I, we defined a LASSO condition number and developed -
WHEN CAN YOU TRUST FEATURE SELECTION? – I: A ...
www.damtp.cam.ac.uk/research/afha/anders/InitialSubmitFeatureSelectionDeterministic.pdf18 Dec 2023: WHEN CAN YOU TRUST FEATURE SELECTION? – I: A CONDITION-BASED ANALYSIS OFLASSO AND GENERALISED HARDNESS OF APPROXIMATION. ALEXANDER BASTOUNIS, FELIPE CUCKER, AND ANDERS C. HANSEN. ABSTRACT. The arrival of AI techniques in computations, with the -
© 2022 European Mathematical SocietyPublished by EMS Press J. ...
www.damtp.cam.ac.uk/user/mjc249/pdfs/JEMS_foundations_colbrook.pdf21 Feb 2023: 2022 European Mathematical SocietyPublished by EMS Press. J. Eur. Math. Soc. (Online first) DOI 10.4171/JEMS/1289. Matthew J. Colbrook Anders C. Hansen. The foundations of spectral computations via theSolvability Complexity Index hierarchy. Received
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