Paper Citation Record · LEDGER

Sparse grids vs. random points for high-dimensional polynomial approximation

As of 17 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 0 inbound Pith citation observations for arXiv:2506.24054.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2506.24054 v1

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measured 53 of 53 reference resolution

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Pith citing papers itemized under the disclosed page cap.

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Reference resolution

53 of 53 outbound references displayed

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External citation measurements

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Outbound references

Observation 25014864-2fe7-415a-82aa-a3d87df2925a · outbound

This paper cites Anderson, Z.

Sparse grids vs. random points for high-dimensional polynomial approximation Anderson, Z

Reference 1

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This paper cites Bartel, M.

Sparse grids vs. random points for high-dimensional polynomial approximation Bartel, M

Reference 2

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Observation 3a438f9f-6c76-438f-8911-071bf64ab124 · outbound

This paper cites Barthelmann, E.

Sparse grids vs. random points for high-dimensional polynomial approximation Barthelmann, E

Reference 3

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Sparse grids vs. random points for high-dimensional polynomial approximation Bos, J.P

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This paper cites Bos, Fekete points as norming sets , Dolomites Research Notes on Approxi- mation, 11(4), 26-–34, 2018, doi: 10.14658/PUPJ-DRNA-2018-4-3.

Sparse grids vs. random points for high-dimensional polynomial approximation Bos, Fekete points as norming sets , Dolomites Research Notes on Approxi- mation, 11(4), 26-–34, 2018, doi: 10.14658/PUPJ-DRNA-2018-4-3

Reference 5

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This paper cites Bos, On optimal designs for a d-cube , Dolomites Research Notes on Ap- proximation, 15(4), 20–34, 2018, doi: 10.14658/PUPJ-DRNA-2022-4-3.

Sparse grids vs. random points for high-dimensional polynomial approximation Bos, On optimal designs for a d-cube , Dolomites Research Notes on Ap- proximation, 15(4), 20–34, 2018, doi: 10.14658/PUPJ-DRNA-2022-4-3

Reference 6

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Sparse grids vs. random points for high-dimensional polynomial approximation Unresolved cited work

Reference 7

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This paper cites Bungartz and M.

Sparse grids vs. random points for high-dimensional polynomial approximation Bungartz and M

Reference 8

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Sparse grids vs. random points for high-dimensional polynomial approximation Becker, O

Reference 9

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Sparse grids vs. random points for high-dimensional polynomial approximation Calvi and N

Reference 10

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Observation 318040fb-2215-41de-9ac1-ed2e85c81421 · outbound

This paper cites Chkifa, A.

Sparse grids vs. random points for high-dimensional polynomial approximation Chkifa, A

Reference 11

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This paper cites Chkifa and M.

Sparse grids vs. random points for high-dimensional polynomial approximation Chkifa and M

Reference 12

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This paper cites Cohen, M.A.

Sparse grids vs. random points for high-dimensional polynomial approximation Cohen, M.A

Reference 13

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Sparse grids vs. random points for high-dimensional polynomial approximation Cohen, G

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This paper cites Coleman and S.

Sparse grids vs. random points for high-dimensional polynomial approximation Coleman and S

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This paper cites Dolbeault and A.

Sparse grids vs. random points for high-dimensional polynomial approximation Dolbeault and A

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This paper cites Dolbeault, D.

Sparse grids vs. random points for high-dimensional polynomial approximation Dolbeault, D

Reference 17

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Sparse grids vs. random points for high-dimensional polynomial approximation Dai and A

Reference 18

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This paper cites D˜ ung, V.

Sparse grids vs. random points for high-dimensional polynomial approximation D˜ ung, V

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Sparse grids vs. random points for high-dimensional polynomial approximation Ehlich and K

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This paper cites Genz, Testing multidimensional integration routines, Proc.

Sparse grids vs. random points for high-dimensional polynomial approximation Genz, Testing multidimensional integration routines, Proc

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This paper cites Kernel interpolation on generalized sparse grids.

Sparse grids vs. random points for high-dimensional polynomial approximation Kernel interpolation on generalized sparse grids

Reference 23

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This paper cites Gr¨ ochenig, Sampling, Marcinkiewicz-Zygmund inequalities, approxima- tion, and quadrature rules , J.

Sparse grids vs. random points for high-dimensional polynomial approximation Gr¨ ochenig, Sampling, Marcinkiewicz-Zygmund inequalities, approxima- tion, and quadrature rules , J

Reference 24

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Observation b233809f-cbb7-45a3-b6eb-4e3e1812db6f · outbound

This paper cites Harris, K.J.Millman and S.

Sparse grids vs. random points for high-dimensional polynomial approximation Harris, K.J.Millman and S

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This paper cites Johnson, Why, when, and how biochemists should use least squares , Ana- lytical biochemistry, 206(2), 215-225, 1992, doi: 10.1016/0003-2697(92)90356-c.

Sparse grids vs. random points for high-dimensional polynomial approximation Johnson, Why, when, and how biochemists should use least squares , Ana- lytical biochemistry, 206(2), 215-225, 1992, doi: 10.1016/0003-2697(92)90356-c

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This paper cites Kashin, S.

Sparse grids vs. random points for high-dimensional polynomial approximation Kashin, S

Reference 29

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Sparse grids vs. random points for high-dimensional polynomial approximation Kashin, E

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Sparse grids vs. random points for high-dimensional polynomial approximation Kro´ o,On optimal polynomial meshes, J

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Sparse grids vs. random points for high-dimensional polynomial approximation Krieg, K

Reference 32

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Sparse grids vs. random points for high-dimensional polynomial approximation Krieg, K

Reference 33

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Sparse grids vs. random points for high-dimensional polynomial approximation Krieg, P

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Sparse grids vs. random points for high-dimensional polynomial approximation Krieg and M

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Sparse grids vs. random points for high-dimensional polynomial approximation Krieg and M

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Sparse grids vs. random points for high-dimensional polynomial approximation Lines and S

Reference 37

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Sparse grids vs. random points for high-dimensional polynomial approximation Migliorati, F

Reference 38

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This paper cites A Christoffel function weighted least squares algorithm for collocation approximations.

Sparse grids vs. random points for high-dimensional polynomial approximation A Christoffel function weighted least squares algorithm for collocation approximations

Reference 39

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Sparse grids vs. random points for high-dimensional polynomial approximation Novak and K

Reference 40

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Sparse grids vs. random points for high-dimensional polynomial approximation Novak and K

Reference 41

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Observation 4b021624-a027-4819-acd7-e2ffe59e6337 · outbound

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Sparse grids vs. random points for high-dimensional polynomial approximation Narayan and Y

Reference 42

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Observation cb195b3d-9c6c-4a4c-baf1-5f983f1abbcc · outbound

This paper cites Reichel On polynomial approximation in the uniform norm by the discrete least squares method , BIT, 26(3), 349–368, 1986, doi: 10.1007/BF01933715.

Sparse grids vs. random points for high-dimensional polynomial approximation Reichel On polynomial approximation in the uniform norm by the discrete least squares method , BIT, 26(3), 349–368, 1986, doi: 10.1007/BF01933715

Reference 43

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Observation ab0bd6cb-9307-4b7b-b0d5-dbc34bc45898 · outbound

This paper cites Smolyak, Quadrature and interpolation formulas for tensor products of certain classes of functions , Dokl.

Sparse grids vs. random points for high-dimensional polynomial approximation Smolyak, Quadrature and interpolation formulas for tensor products of certain classes of functions , Dokl

Reference 44

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Observation 9da39065-d5a3-4dcf-aeb7-02f52e61e3ca · outbound

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Sparse grids vs. random points for high-dimensional polynomial approximation Sonnleitner, M

Reference 45

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Observation 5a5e59b8-c48d-4262-834a-44a2d044f623 · outbound

This paper cites Stoyanov, User manual: TASMANIAN sparse grids , ORNL/TM- 2015/596, 2015.

Sparse grids vs. random points for high-dimensional polynomial approximation Stoyanov, User manual: TASMANIAN sparse grids , ORNL/TM- 2015/596, 2015

Reference 46

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Sparse grids vs. random points for high-dimensional polynomial approximation Stoyanov, D

Reference 47

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Observation 4d9f34ce-aeb3-409e-a508-a728248eadfd · outbound

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Sparse grids vs. random points for high-dimensional polynomial approximation Surjanovic and D

Reference 48

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Reference 49

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Observation 55ca56da-9e4e-42cc-9eb7-3b103357ce20 · outbound

This paper cites Temlyakov, Approximation of periodic functions of several variables by trigonometric polynomials, and widths of some classes of functions , Math.

Sparse grids vs. random points for high-dimensional polynomial approximation Temlyakov, Approximation of periodic functions of several variables by trigonometric polynomials, and widths of some classes of functions , Math

Reference 50

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Observation 7f04541a-8b98-4725-b19b-2dcdb922b93e · outbound

This paper cites Ullrich, On the worst-case error of least squares algorithms for L2- approximation with high probability , J.

Sparse grids vs. random points for high-dimensional polynomial approximation Ullrich, On the worst-case error of least squares algorithms for L2- approximation with high probability , J

Reference 51

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Observation 21594010-7237-4172-9851-6cc50b48ff88 · outbound

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Sparse grids vs. random points for high-dimensional polynomial approximation Virtanen, R

Reference 52

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Sparse grids vs. random points for high-dimensional polynomial approximation Wasilkowski and H

Reference 53

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