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.