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ORCIDAlexander Kuhnle
This is just a disambiguation page, and is not intended to be the bibliography of an actual person. Any publication listed on this page has not been assigned to an actual author yet. If you know the true author of one of the publications listed below, you are welcome to contact us.
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Books and Theses
- 2020
[b1]Alexander Kuhnle:
Evaluating visually grounded language capabilities using microworlds. University of Cambridge, UK, 2020
Journal Articles
- 2023
- [j2]Jonathan Viquerat
, Régis Duvigneau, P. Meliga, Alexander Kuhnle, Elie Hachem:
Policy-based optimization: single-step policy gradient method seen as an evolution strategy. Neural Comput. Appl. 35(1): 449-467 (2023) - 2021
- [j1]Jonathan Viquerat, Jean Rabault, Alexander Kuhnle, Hassan Ghraieb, Aurélien Larcher, Elie Hachem:
Direct shape optimization through deep reinforcement learning. J. Comput. Phys. 428: 110080 (2021)
Conference and Workshop Papers
- 2021
- [c7]Alessandro Sestini, Alexander Kuhnle, Andrew D. Bagdanov:
Demonstration-Efficient Inverse Reinforcement Learning in Procedurally Generated Environments. CoG 2021: 1-8 - [c6]Alessandro Sestini, Alexander Kuhnle, Andrew D. Bagdanov:
Policy Fusion for Adaptive and Customizable Reinforcement Learning Agents. CoG 2021: 1-8 - [c5]Alexander Kuhnle, Miguel Aroca-Ouellette, Anindya Basu, Murat Sensoy, John Reid, Dell Zhang:
Reinforcement Learning for Information Retrieval. SIGIR 2021: 2669-2672 - 2019
- [c4]Alexander Kuhnle, Ann A. Copestake:
The Meaning of "Most" for Visual Question Answering Models. BlackboxNLP@ACL 2019: 46-55 - 2018
- [c3]Alexander Kuhnle, Huiyuan Xie, Ann A. Copestake:
How Clever Is the FiLM Model, and How Clever Can it Be? ECCV Workshops (4) 2018: 162-172 - 2016
- [c2]Yimai Fang, Haoyue Zhu, Ewa Muszynska, Alexander Kuhnle, Simone Teufel:
A Proposition-Based Abstractive Summariser. COLING 2016: 567-578 - [c1]Ann A. Copestake, Guy Emerson, Michael Wayne Goodman, Matic Horvat, Alexander Kuhnle, Ewa Muszynska:
Resources for building applications with Dependency Minimal Recursion Semantics. LREC 2016
Informal and Other Publications
- 2022
- [i16]Fabio Pino, Lorenzo Schena, Jean Rabault, Alexander Kuhnle, Miguel A. Mendez:
Comparative analysis of machine learning methods for active flow control. CoRR abs/2202.11664 (2022) - 2021
- [i15]Alessandro Sestini, Alexander Kuhnle, Andrew D. Bagdanov:
Policy Fusion for Adaptive and Customizable Reinforcement Learning Agents. CoRR abs/2104.10610 (2021) - 2020
- [i14]Dell Zhang, Alexander Kuhnle, Julian Richardson, Murat Sensoy:
Process Discovery for Structured Program Synthesis. CoRR abs/2008.05804 (2020) - [i13]Alessandro Sestini, Alexander Kuhnle, Andrew D. Bagdanov:
DeepCrawl: Deep Reinforcement Learning for Turn-based Strategy Games. CoRR abs/2012.01914 (2020) - [i12]Alessandro Sestini, Alexander Kuhnle, Andrew D. Bagdanov:
Demonstration-efficient Inverse Reinforcement Learning in Procedurally Generated Environments. CoRR abs/2012.02527 (2020) - [i11]Alessandro Sestini, Alexander Kuhnle, Andrew D. Bagdanov:
Deep Policy Networks for NPC Behaviors that Adapt to Changing Design Parameters in Roguelike Games. CoRR abs/2012.03532 (2020) - 2019
- [i10]Alexander Kuhnle, Ann A. Copestake:
What is needed for simple spatial language capabilities in VQA? ViGIL@NeurIPS 2019 - [i9]Paul Garnier, Jonathan Viquerat, Jean Rabault, Aurélien Larcher, Alexander Kuhnle, Elie Hachem:
A review on Deep Reinforcement Learning for Fluid Mechanics. CoRR abs/1908.04127 (2019) - [i8]Alexander Kuhnle, Ann A. Copestake:
What is needed for simple spatial language capabilities in VQA? CoRR abs/1908.06336 (2019) - [i7]Jonathan Viquerat, Jean Rabault, Alexander Kuhnle, Hassan Ghraieb, Elie Hachem:
Direct shape optimization through deep reinforcement learning. CoRR abs/1908.09885 (2019) - [i6]Huiyuan Xie, Tom Sherborne, Alexander Kuhnle, Ann A. Copestake:
Going Beneath the Surface: Evaluating Image Captioning for Grammaticality, Truthfulness and Diversity. CoRR abs/1912.08960 (2019) - 2018
- [i5]Michael Schaarschmidt, Alexander Kuhnle, Ben Ellis, Kai Fricke, Felix Gessert, Eiko Yoneki:
LIFT: Reinforcement Learning in Computer Systems by Learning From Demonstrations. CoRR abs/1808.07903 (2018) - [i4]Alexander Kuhnle, Huiyuan Xie, Ann A. Copestake:
How clever is the FiLM model, and how clever can it be? CoRR abs/1809.03044 (2018) - [i3]Alexander Kuhnle, Ann A. Copestake:
The meaning of "most" for visual question answering models. CoRR abs/1812.11737 (2018) - 2017
- [i2]Alexander Kuhnle, Ann A. Copestake:
ShapeWorld - A new test methodology for multimodal language understanding. CoRR abs/1704.04517 (2017) - [i1]Alexander Kuhnle, Ann A. Copestake:
Deep learning evaluation using deep linguistic processing. CoRR abs/1706.01322 (2017)
Coauthor Index
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