Results 241 to 250 of about 39,214 (275)

Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators

Nature Machine Intelligence, 2021
Lu Lu, Pengzhan Jin, Guofei Pang
exaly  

Automated Theorem Proving with Web Services

2013
Automated theorem provers (ATP) usually operate on finite input where all relevant axioms and conjectures are known at the start of the proof attempt. However, when a prover is embedded in a real-world knowledge representation application, it may have to draw upon data that is not immediately available in a local file, for example by accessing ...
openaire   +1 more source

Experimental quantum key distribution certified by Bell's theorem

Nature, 2022
David Nadlinger, C j Ballance, Kirill Ivanov   +2 more
exaly  

On Automated Theorem Proving

Annals of the New York Academy of Sciences, 1992
STEPHEN RUSSELL, TRACI WHEELER UNISYS
openaire   +1 more source

Orderings in Automated Theorem Proving

1998
This paper is intended to give an introduction to several techniques used in automated theorem proving, and based on the concept of ordering on terms and more generally on formulas. Different orderings and their automation are presented and several applications are considered.
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Automated Theorem Proving with Disjunctive Constraints

1999
Automated theorem proving (ATP) is an important research area in artificial intelligence. The objective of an ATP system is to find out whether or not a query (or goal) is a logical consequence of a set of axioms (the query and the axioms have to be formally specified, for example in first-order clause logic).
openaire   +1 more source

Verification of the Crooks fluctuation theorem and recovery of RNA folding free energies

Nature, 2005
Felix Ritort, Christopher Jarzynski
exaly  

Automated Theorem Proving

1982
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Automated Theorem Proving and Machine Learning

In this thesis, we present a framework for Automated Theorem Proving called plCoP, which builds on theleanCoP system and adds machine learning-guided Monte Carlo TreeSearch.
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A new fixed-time stability theorem and its application to the fixed-time synchronization of neural networks

Neural Networks, 2020
Chuan Chen, Lixiang Li, Haipeng Peng
exaly