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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Uncertainty Quantification and Uncertainty Propagation Under Traditional and Ai-Based Data Processing (and Related Topics): Legacy of Grigory Tseytin

Uncertainty Quantification and Uncertainty Propagation Under Traditional and Ai-Based Data Processing (and Related Topics): Legacy of Grigory Tseytin

Kreinovich, Vladik
Dantsin, Evgeny

Hardcover

Series: Studies in Systems, Decision and Control, Book 660

Technology & EngineeringGeneral Computers

ISBN10: 3032164931
ISBN13: 9783032164933
Publisher: Springer
Published: Jul 17 2026
Pages: 351
Weight: 1.44
Height: 0.96 Width: 6.47 Depth: 9.33
Language: English
Why revisit uncertainty? Data processing is now often performed by Large Language Models (LLMs) and other AI tools that use natural-language texts. Many LLMs' results are spectacular, but often, there is no good indication of their accuracy. We need to revisit traditional methods for quantifying and propagating uncertainty, to see how they can help with these new challenges.

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