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 • 15 Mar 2023 • Brando Miranda, Avi Shinnar, Vasily Pestun, Barry Trager
Despite a growing body of work at the intersection of deep learning and formal languages, there has been relatively little systematic exploration of transformer models for reasoning about typed lambda calculi.
1 code implementation • 12 Feb 2022 • Koundinya Vajjha, Barry Trager, Avraham Shinnar, Vasily Pestun
Stochastic approximation algorithms are iterative procedures which are used to approximate a target value in an environment where the target is unknown and direct observations are corrupted by noise.
1 code implementation • 23 Sep 2020 • Koundinya Vajjha, Avraham Shinnar, Vasily Pestun, Barry Trager, Nathan Fulton
Reinforcement learning algorithms solve sequential decision-making problems in probabilistic environments by optimizing for long-term reward.
no code implementations • 4 Nov 2017 • Vasily Pestun, John Terilla, Yiannis Vlassopoulos
We propose a statistical model for natural language that begins by considering language as a monoid, then representing it in complex matrices with a compatible translation invariant probability measure.
no code implementations • 27 Oct 2017 • Vasily Pestun, Yiannis Vlassopoulos
We propose a new statistical model suitable for machine learning of systems with long distance correlations such as natural languages.