4 papers
TubeDAgger: Reducing the Number of Expert Interventions with Stochastic Reach-Tubes
Julian Lemmel, Manuel Kranzl, Adam Lamine +3
Interactive Imitation Learning deals with training a novice policy from expert demonstrations in an online fashion. The established DAgger algorithm trains a robust novice policy b…
Liquid Resistance Liquid Capacitance Networks
Mónika Farsang, Sophie A. Neubauer, Radu Grosu
We introduce liquid-resistance liquid-capacitance neural networks (LRCs), a neural-ODE model which considerably improve the generalization, accuracy, and biological plausibility of…
Online Fine-Tuning of Carbon Emission Predictions using Real-Time Recurrent Learning for State Space Models
Julian Lemmel, Manuel Kranzl, Adam Lamine +3
This paper introduces a new approach for fine-tuning the predictions of structured state space models (SSMs) at inference time using real-time recurrent learning. While SSMs are kn…
Scalable Offline Reinforcement Learning for Mean Field Games
Axel Brunnbauer, Julian Lemmel, Zahra Babaiee +2
Reinforcement learning algorithms for mean-field games offer a scalable framework for optimizing policies in large populations of interacting agents. Existing methods often depend…