David Leeftink
@davidleeftink.bsky.social
PhD student in Machine learning @ Donders Institute Nijmegen | Probabilistic Machine Learning, Control, Reinforcement Learning.
Pinned
Our recent paper “Optimal Control of Probabilistic Dynamics Models via Mean Hamiltonian Minimization,” has been accepted to CDC 2025!
We demonstrate how applying optimal control principles can significantly improve planning in deep model-based reinforcement learning with epistemic uncertainty.
We demonstrate how applying optimal control principles can significantly improve planning in deep model-based reinforcement learning with epistemic uncertainty.
Reposted by David Leeftink
Against Publishing: universonline.nl/nieuws/2025/...
Preprints are read, shared, and cited, yet still dismissed as incomplete until blessed by a publisher. I argue that the true measure of scholarship lies in open exchange, not in the industry’s gatekeeping of what counts as published.
Preprints are read, shared, and cited, yet still dismissed as incomplete until blessed by a publisher. I argue that the true measure of scholarship lies in open exchange, not in the industry’s gatekeeping of what counts as published.
October 14, 2025 at 9:16 AM
Against Publishing: universonline.nl/nieuws/2025/...
Preprints are read, shared, and cited, yet still dismissed as incomplete until blessed by a publisher. I argue that the true measure of scholarship lies in open exchange, not in the industry’s gatekeeping of what counts as published.
Preprints are read, shared, and cited, yet still dismissed as incomplete until blessed by a publisher. I argue that the true measure of scholarship lies in open exchange, not in the industry’s gatekeeping of what counts as published.
Our recent paper “Optimal Control of Probabilistic Dynamics Models via Mean Hamiltonian Minimization,” has been accepted to CDC 2025!
We demonstrate how applying optimal control principles can significantly improve planning in deep model-based reinforcement learning with epistemic uncertainty.
We demonstrate how applying optimal control principles can significantly improve planning in deep model-based reinforcement learning with epistemic uncertainty.
September 3, 2025 at 2:57 PM
Our recent paper “Optimal Control of Probabilistic Dynamics Models via Mean Hamiltonian Minimization,” has been accepted to CDC 2025!
We demonstrate how applying optimal control principles can significantly improve planning in deep model-based reinforcement learning with epistemic uncertainty.
We demonstrate how applying optimal control principles can significantly improve planning in deep model-based reinforcement learning with epistemic uncertainty.