no code implementations • 5 Jan 2024 • Jason Rute, Miroslav Olšák, Lasse Blaauwbroek, Fidel Ivan Schaposnik Massolo, Jelle Piepenbrock, Vasily Pestun

G2T is an online model that is deeply integrated into the users' workflow and can adapt in real time to new Coq projects and their definitions.

no code implementations • 27 Jan 2023 • Thibault Gauthier, Miroslav Olšák, Josef Urban

We introduce a self-learning algorithm for synthesizing programs for OEIS sequences.

1 code implementation • 7 Oct 2022 • Jelle Piepenbrock, Josef Urban, Konstantin Korovin, Miroslav Olšák, Tom Heskes, Mikolaš Janota

In particular, we develop a GNN2RNN architecture based on an invariant graph neural network (GNN) that learns from problems and their solutions independently of symbol names (addressing the abundance of skolems), combined with a recurrent neural network (RNN) that proposes for each clause its instantiations.

1 code implementation • 4 May 2022 • Zarathustra A. Goertzel, Jan Jakubův, Cezary Kaliszyk, Miroslav Olšák, Jelle Piepenbrock, Josef Urban

We significantly improve the performance of the E automated theorem prover on the Isabelle Sledgehammer problems by combining learning and theorem proving in several ways.

1 code implementation • 21 Jul 2021 • Karel Chvalovský, Jan Jakubův, Miroslav Olšák, Josef Urban

Saturation-style automated theorem provers (ATPs) based on the given clause procedure are today the strongest general reasoners for classical first-order logic.

1 code implementation • 14 Jul 2021 • Zarathustra Goertzel, Karel Chvalovský, Jan Jakubův, Miroslav Olšák, Josef Urban

The second addition is motivated by fast weight-based rejection filters that are currently used in systems like E and Prover9.

no code implementations • 31 May 2021 • Zsolt Zombori, Josef Urban, Miroslav Olšák

This leads us to explore how the entropy of the inference selection implemented via the neural network influences the proof search.

no code implementations • 13 Jun 2020 • Manuel Bodirsky, Antoine Mottet, Miroslav Olšák, Jakub Opršal, Michael Pinsker, Ross Willard

The algebraic dichotomy conjecture for Constraint Satisfaction Problems (CSPs) of reducts of (infinite) finitely bounded homogeneous structures states that such CSPs are polynomial-time tractable if the model-complete core of the template has a pseudo-Siggers polymorphism, and NP-complete otherwise.

Logic Logic in Computer Science Rings and Algebras

no code implementations • 13 Feb 2020 • Jan Jakubův, Karel Chvalovský, Miroslav Olšák, Bartosz Piotrowski, Martin Suda, Josef Urban

For the neural guidance, we use symbol-independent graph neural networks (GNNs) and their embedding of the terms and clauses.

no code implementations • 27 Nov 2019 • Miroslav Olšák, Cezary Kaliszyk, Josef Urban

This encoding represents symbols only by nodes in the graph, without giving the network any knowledge of the original labels.

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