On the public citation graph
A New Distillation Algorithm for Floating-Point Summation
0 signed · 32 inferred · view as graph
Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.
Is this your work? Sign in with ORCID and put your name on the
claims that are yours.
Reference health. See whether every reference in this work resolves to a
known work and none has been retracted — and get a dated CiteStamped
badge you can embed.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/zamm.19740540106openalex-snapshot
Rundungsfehleranalyse einiger Verfahren zur Summation endlicher Summen
inferredcites →https://doi.org/10.1007/bf01397083openalex-snapshot
A floating-point technique for extending the available precision
inferredcites →https://doi.org/10.1109/arith.1991.145549openalex-snapshot
Algorithms for arbitrary precision floating point arithmetic
inferredcites →https://doi.org/10.1137/0914050openalex-snapshot
The Accuracy of Floating Point Summation
inferredcites →https://doi.org/10.1137/1.9780898718027openalex-snapshot
Accuracy and Stability of Numerical Algorithms
inferredcites →https://doi.org/10.1137/s1064827502407627openalex-snapshot
Accurate and Efficient Floating Point Summation
inferredcites →https://doi.org/10.1137/s1064827596314200openalex-snapshot
A Distillation Algorithm for Floating-Point Summation
inferredcites →https://doi.org/10.1145/103162.103163openalex-snapshot
What every computer scientist should know about floating-point arithmetic
inferredcites →https://doi.org/10.1145/361573.361584openalex-snapshot
A comparison of floating point summation methods
inferredcites →https://doi.org/10.1145/362384.362498openalex-snapshot
Accurate floating-point summation
inferredcites →https://doi.org/10.1145/362854.362889openalex-snapshot
On accurate floating-point summation
inferredcites →https://doi.org/10.1145/363707.363723openalex-snapshot
Pracniques: further remarks on reducing truncation errors
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-3-642-38756-2_29openalex-snapshot
On the Complexity of Approximate Sum of Sorted List
inferred← citeshttps://doi.org/10.1007/s00607-005-0120-8openalex-snapshot
Line Segment Intersection Testing
inferred← citeshttps://doi.org/10.1016/j.cam.2012.10.010openalex-snapshot
Accurate solution of dense linear systems, part I: Algorithms in rounding to nearest
inferred← citeshttps://doi.org/10.1017/s096249291000005xopenalex-snapshot
Verification methods: Rigorous results using floating-point arithmetic
inferred← citeshttps://doi.org/10.1109/arith.2009.16openalex-snapshot
On the Computation of Correctly-Rounded Sums
inferred← citeshttps://doi.org/10.1109/ispdc.2010.12openalex-snapshot
Pretty Good Accuracy in Matrix Multiplication with GPUs
inferred← citeshttps://doi.org/10.1109/tc.2011.27openalex-snapshot
On the Computation of Correctly Rounded Sums
inferred← citeshttps://doi.org/10.1109/telfor.2015.7377518openalex-snapshot
One solution of the accurate summation using fixed-point accumulator
inferred← citeshttps://doi.org/10.1137/050645671openalex-snapshot
Accurate Floating-Point Summation Part I: Faithful Rounding
inferred← citeshttps://doi.org/10.1137/07068816xopenalex-snapshot
Accurate Floating-Point Summation Part II: Sign, K -Fold Faithful and Rounding to Nearest
inferred← citeshttps://doi.org/10.1137/070710020openalex-snapshot
Correct Rounding and a Hybrid Approach to Exact Floating-Point Summation
inferred← citeshttps://doi.org/10.1137/25m1722573openalex-snapshot
Verified Error Bounds for Sparse Systems Part I: The Splitting of a Matrix into Two Factors
inferred← citeshttps://doi.org/10.1155/2011/417569openalex-snapshot
Improving Accuracy for Matrix Multiplications on GPUs
inferred← citeshttps://doi.org/10.70675/a8714c7dz67bdz4a72z9630zb0e101d80169openalex-snapshot
Towards reproducible, accurately rounded and efficient BLAS
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.