1 citations · 2 across the 5 of their papers we have counts for
3 papers · 1 filter
Simulation Priors for Data-Efficient Deep Learning
Lenart Treven, Bhavya Sukhija, Jonas Rothfuss +3
How do we enable AI systems to efficiently learn in the real-world? First-principles models are widely used to simulate natural systems, but often fail to capture real-world comple…
NeoRL: Efficient Exploration for Nonepisodic RL
Bhavya Sukhija, Lenart Treven, Florian Dörfler +2
We study the problem of nonepisodic reinforcement learning (RL) for nonlinear dynamical systems, where the system dynamics are unknown and the RL agent has to learn from a single t…
Distributional Gradient Matching for Learning Uncertain Neural Dynamics Models
Lenart Treven, Philippe Wenk, Florian Dörfler +1
Differential equations in general and neural ODEs in particular are an essential technique in continuous-time system identification. While many deterministic learning algorithms ha…