Alexander Kuhnle

26 papers A* 1B 2C 2Journal 17Unranked 3

Year	Rank	Type	Title / Venue / Authors
2023	J	`jnl`	Policy-based optimization: single-step policy gradient method seen as an evolution strategy. Neural Comput. Appl. Jonathan Viquerat, Régis Duvigneau, P. Meliga, Alexander Kuhnle, Elie Hachem
2022	J	`jnl`	Comparative analysis of machine learning methods for active flow control. CoRR Fabio Pino, Lorenzo Schena, Jean Rabault, Alexander Kuhnle, Miguel A. Mendez
2021	C	`conf`	Demonstration-Efficient Inverse Reinforcement Learning in Procedurally Generated Environments. CoG Alessandro Sestini, Alexander Kuhnle, Andrew D. Bagdanov
2021	J	`jnl`	Direct shape optimization through deep reinforcement learning. J. Comput. Phys. Jonathan Viquerat, Jean Rabault, Alexander Kuhnle, Hassan Ghraieb, Aurélien Larcher, Elie Hachem
2021	C	`conf`	Policy Fusion for Adaptive and Customizable Reinforcement Learning Agents. CoG Alessandro Sestini, Alexander Kuhnle, Andrew D. Bagdanov
2021	J	`jnl`	Policy Fusion for Adaptive and Customizable Reinforcement Learning Agents. CoRR Alessandro Sestini, Alexander Kuhnle, Andrew D. Bagdanov
2021	A*	`conf`	Reinforcement Learning for Information Retrieval. SIGIR Alexander Kuhnle, Miguel Aroca-Ouellette, Anindya Basu, Murat Sensoy, John Reid, Dell Zhang
2020	J	`jnl`	Deep Policy Networks for NPC Behaviors that Adapt to Changing Design Parameters in Roguelike Games. CoRR Alessandro Sestini, Alexander Kuhnle, Andrew D. Bagdanov
2020	J	`jnl`	DeepCrawl: Deep Reinforcement Learning for Turn-based Strategy Games. CoRR Alessandro Sestini, Alexander Kuhnle, Andrew D. Bagdanov
2020	J	`jnl`	Demonstration-efficient Inverse Reinforcement Learning in Procedurally Generated Environments. CoRR Alessandro Sestini, Alexander Kuhnle, Andrew D. Bagdanov
2020	—	`—`	Evaluating visually grounded language capabilities using microworlds. Alexander Kuhnle
2020	J	`jnl`	Process Discovery for Structured Program Synthesis. CoRR Dell Zhang, Alexander Kuhnle, Julian Richardson, Murat Sensoy
2019	J	`jnl`	A review on Deep Reinforcement Learning for Fluid Mechanics. CoRR Paul Garnier, Jonathan Viquerat, Jean Rabault, Aurélien Larcher, Alexander Kuhnle, Elie Hachem
2019	J	`jnl`	Direct shape optimization through deep reinforcement learning. CoRR Jonathan Viquerat, Jean Rabault, Alexander Kuhnle, Hassan Ghraieb, Elie Hachem
2019	J	`jnl`	Going Beneath the Surface: Evaluating Image Captioning for Grammaticality, Truthfulness and Diversity. CoRR Huiyuan Xie, Tom Sherborne, Alexander Kuhnle, Ann A. Copestake
2019	—	`conf`	The Meaning of "Most" for Visual Question Answering Models. BlackboxNLP@ACL Alexander Kuhnle, Ann A. Copestake
2019	—	`conf`	What is needed for simple spatial language capabilities in VQA? ViGIL@NeurIPS Alexander Kuhnle, Ann A. Copestake
2019	J	`jnl`	What is needed for simple spatial language capabilities in VQA? CoRR Alexander Kuhnle, Ann A. Copestake
2018	—	`conf`	How Clever Is the FiLM Model, and How Clever Can it Be? ECCV Workshops (4) Alexander Kuhnle, Huiyuan Xie, Ann A. Copestake
2018	J	`jnl`	How clever is the FiLM model, and how clever can it be? CoRR Alexander Kuhnle, Huiyuan Xie, Ann A. Copestake
2018	J	`jnl`	LIFT: Reinforcement Learning in Computer Systems by Learning From Demonstrations. CoRR Michael Schaarschmidt, Alexander Kuhnle, Ben Ellis, Kai Fricke, Felix Gessert, Eiko Yoneki
2018	J	`jnl`	The meaning of "most" for visual question answering models. CoRR Alexander Kuhnle, Ann A. Copestake
2017	J	`jnl`	Deep learning evaluation using deep linguistic processing. CoRR Alexander Kuhnle, Ann A. Copestake
2017	J	`jnl`	ShapeWorld - A new test methodology for multimodal language understanding. CoRR Alexander Kuhnle, Ann A. Copestake
2016	B	`conf`	A Proposition-Based Abstractive Summariser. COLING Yimai Fang, Haoyue Zhu, Ewa Muszynska, Alexander Kuhnle, Simone Teufel
2016	B	`conf`	Resources for building applications with Dependency Minimal Recursion Semantics. LREC Ann A. Copestake, Guy Emerson, Michael Wayne Goodman, Matic Horvat, Alexander Kuhnle, Ewa Muszynska