Mathematical Proofs
17 papers with code • 0 benchmarks • 2 datasets
Benchmarks
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NaturalProofs
Latest papers with no code
How Deduction Systems Can Help You To Verify Stability Properties
Mathematical proofs are a cornerstone of control theory, and it is important to get them right.
A Semantic Search Engine for Mathlib4
In this paper, we present a semantic search engine for mathlib4 that accepts informal queries and finds the relevant theorems.
Class Information Guided Reconstruction for Automatic Modulation Open-Set Recognition
To enhance distinguishability, we design Class Conditional Vectors (CCVs) to match the latent representations extracted from input samples, achieving perfect reconstruction for known samples while yielding poor results for unknown ones.
Automated Planning Techniques for Elementary Proofs in Abstract Algebra
This paper explores the application of automated planning to automated theorem proving, which is a branch of automated reasoning concerned with the development of algorithms and computer programs to construct mathematical proofs.
FastPart: Over-Parameterized Stochastic Gradient Descent for Sparse optimisation on Measures
This paper presents a novel algorithm that leverages Stochastic Gradient Descent strategies in conjunction with Random Features to augment the scalability of Conic Particle Gradient Descent (CPGD) specifically tailored for solving sparse optimisation problems on measures.
Large Language Models' Understanding of Math: Source Criticism and Extrapolation
We also see that GPT-4's ability to prove mathematical theorems is continuously expanding over time despite the claim that it is a fixed model.
Characterizing the Conditions for Indefinite Growth in Open Chemical Reaction Networks
Within multimolecular CRNs, pseudo-unimolecular CRNs produce nonequilibrium concentrations with zero efficiencies.
Total-effect Test May Erroneously Reject So-called "Full" or "Complete" Mediation
The procedure for establishing mediation, i. e., determining that an independent variable X affects a dependent variable Y through some mediator M, has been under debate.
Anomaly zones for uniformly sampled gene trees under the gene duplication and loss model
The gene duplication and loss process is a generalization of the generalized linear-birth death process to the rooted species tree, where each edge is treated as a single timeline with exponential-rate duplication and loss.
An Efficient Data Analysis Method for Big Data using Multiple-Model Linear Regression
This paper introduces a new data analysis method for big data using a newly defined regression model named multiple model linear regression(MMLR), which separates input datasets into subsets and construct local linear regression models of them.
