95 citations · 169 across the 14 of their papers we have counts for
5 papers · 1 filter
Red-Teaming the Stable Diffusion Safety Filter
Javier Rando, Daniel Paleka, David Lindner +2
Stable Diffusion is a recent open-source image generation model comparable to proprietary models such as DALLE, Imagen, or Parti. Stable Diffusion comes with a safety filter that a…
Active Exploration for Inverse Reinforcement Learning
David Lindner, Andreas Krause, Giorgia Ramponi
Inverse Reinforcement Learning (IRL) is a powerful paradigm for inferring a reward function from expert demonstrations. Many IRL algorithms require a known transition model and som…
Humans are not Boltzmann Distributions: Challenges and Opportunities for Modelling Human Feedback and Interaction in Reinforcement Learning
David Lindner, Mennatallah El-Assady
Reinforcement learning (RL) commonly assumes access to well-specified reward functions, which many practical applications do not provide. Instead, recently, more work has explored…
Interactively Learning Preference Constraints in Linear Bandits
David Lindner, Sebastian Tschiatschek, Katja Hofmann +1
We study sequential decision-making with known rewards and unknown constraints, motivated by situations where the constraints represent expensive-to-evaluate human preferences, suc…
GoSafeOpt: Scalable Safe Exploration for Global Optimization of Dynamical Systems
Bhavya Sukhija, Matteo Turchetta, David Lindner +3
Learning optimal control policies directly on physical systems is challenging since even a single failure can lead to costly hardware damage. Most existing model-free learning meth…