Tobias Pohlen — accepted AI-conference papers

2022

A data-driven approach for learning to control computers

Peter C Humphreys, David Raposo, Tobias Pohlen, Gregory Thornton, Rachita Chhaparia, Alistair Muldal +4

ICML 2022spotlight

It would be useful for machines to use computers as humans do so that they can aid us in everyday tasks. This is a setting in which there is also the potential to leverage large-scale expert demonstrations and human judgements of interactive behaviour, which are two ingredients that have driven much…

Cited by 119 Source ↗PDF ↗Scholar ↗

2018

Reward learning from human preferences and demonstrations in Atari

Borja Ibarz, Jan Leike, Tobias Pohlen, Geoffrey Irving, Shane Legg, Dario Amodei

NeurIPS 2018poster

To solve complex real-world problems with reinforcement learning, we cannot rely on manually specified reward functions. Instead, we need humans to communicate an objective to the agent directly. In this work, we combine two approaches to this problem: learning from expert demonstrations and learnin…

Cited by 504 Source ↗PDF ↗Scholar ↗

2017

Full-Resolution Residual Networks for Semantic Segmentation in Street Scenes

Tobias Pohlen, Alexander Hermans, Markus Mathias, Bastian Leibe

CVPR 2017oral

Semantic image segmentation is an essential component of modern autonomous driving systems, as an accurate understanding of the surrounding scene is crucial to navigation and action planning. Current state-of-the-art approaches in semantic image segmentation rely on pre-trained networks that were in…

Cited by 741 PDF ↗code ↗Scholar ↗