no code implementations • 30 Jan 2024 • Mónika Farsang, Radu Grosu
By observing that the TG corresponds to the forget gate (FG) in traditional gated recurrent units, we provide a new formulation of these units as neural ODEs.
no code implementations • 21 Nov 2023 • Mónika Farsang, Mathias Lechner, David Lung, Ramin Hasani, Daniela Rus, Radu Grosu
In this work we aim to determine the impact of using chemical synapses compared to electrical synapses, in both sparse and all-to-all connected networks.
1 code implementation • 24 Oct 2022 • Mónika Farsang, Paul Mineiro, Wangda Zhang
Contextual bandits with average-case statistical guarantees are inadequate in risk-averse situations because they might trade off degraded worst-case behaviour for better average performance.
1 code implementation • 20 Feb 2021 • Mónika Farsang, Luca Szegletes
Proximal Policy Optimization (PPO) is among the most widely used algorithms in reinforcement learning, which achieves state-of-the-art performance in many challenging problems.
no code implementations • 20 Feb 2021 • Mónika Farsang, Luca Szegletes
An in-depth understanding of the particular environment is crucial in reinforcement learning (RL).