Alexander Kuhnle
Alexander Kuhnle
Blue Prism
Verified email at cam.ac.uk - Homepage
Title
Cited by
Cited by
Year
Tensorforce: a TensorFlow library for applied reinforcement learning
A Kuhnle, M Schaarschmidt, K Fricke
Web page, 2017
54*2017
Accelerating deep reinforcement learning strategies of flow control through a multi-environment approach
J Rabault, A Kuhnle
Physics of Fluids 31 (9), 094105, 2019
242019
Accelerating deep reinforcement learning strategies of flow control through a multi-environment approach
J Rabault, A Kuhnle
Physics of Fluids 31 (9), 094105, 2019
242019
ShapeWorld-A new test methodology for multimodal language understanding
A Kuhnle, A Copestake
arXiv preprint arXiv:1704.04517, 2017
242017
Resources for building applications with Dependency Minimal Recursion Semantics
A Copestake, G Emerson, MW Goodman, M Horvat, A Kuhnle, ...
Proceedings of the Tenth Language Resources and Evaluation Conference (LREC’16), 2016
242016
Robust active flow control over a range of Reynolds numbers using an artificial neural network trained through deep reinforcement learning
H Tang, J Rabault, A Kuhnle, Y Wang, T Wang
Physics of Fluids 32 (5), 053605, 2020
232020
LIFT: Reinforcement Learning in Computer Systems by Learning From Demonstrations
M Schaarschmidt, A Kuhnle, B Ellis, K Fricke, F Gessert, E Yoneki
arXiv preprint arXiv:1808.07903, 2018
202018
A Proposition-Based Abstractive Summariser
Y Fang, H Zhu, E Muszynska, A Kuhnle, S Teufel
15*
Direct shape optimization through deep reinforcement learning
J Viquerat, J Rabault, A Kuhnle, H Ghraieb, A Larcher, E Hachem
Journal of Computational Physics, 110080, 2020
142020
A review on Deep Reinforcement Learning for Fluid Mechanics
P Garnier, J Viquerat, J Rabault, A Larcher, A Kuhnle, E Hachem
arXiv preprint arXiv:1908.04127, 2019
142019
Deep learning evaluation using deep linguistic processing
A Kuhnle, A Copestake
arXiv preprint arXiv:1706.01322, 2017
82017
How clever is the FiLM model, and how clever can it be?
A Kuhnle, H Xie, A Copestake
European Conference on Computer Vision, 162-172, 2018
52018
Going Beneath the Surface: Evaluating Image Captioning for Grammaticality, Truthfulness and Diversity
H Xie, T Sherborne, A Kuhnle, A Copestake
arXiv preprint arXiv:1912.08960, 2019
32019
DeepCrawl: Deep Reinforcement Learning for Turn-based Strategy Games
A Sestini, A Kuhnle, AD Bagdanov
arXiv preprint arXiv:2012.01914, 2020
22020
Modeling uncertain data using monads and an application to the sequence alignment problem
A Kuhnle
Master’s thesis, Karlsruhe Institute of Technology, 2013
22013
DEEP REINFORCEMENT LEARNING APPLIED TO ACTIVE FLOW CONTROL
J Rabault, A Kuhnle
12020
The meaning of" most" for visual question answering models
A Kuhnle, A Copestake
arXiv preprint arXiv:1812.11737, 2018
12018
The meaning of" most" for visual question answering models
A Kuhnle, A Copestake
arXiv preprint arXiv:1812.11737, 2018
12018
Deep Policy Networks for NPC Behaviors that Adapt to Changing Design Parameters in Roguelike Games
A Sestini, A Kuhnle, AD Bagdanov
arXiv preprint arXiv:2012.03532, 2020
2020
Demonstration-efficient Inverse Reinforcement Learning in Procedurally Generated Environments
A Sestini, A Kuhnle, AD Bagdanov
arXiv preprint arXiv:2012.02527, 2020
2020
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Articles 1–20