Publications

Joel Jonsson, Bevan Leslie Cheeseman, and Ivo Sbalzarini. APR-CNN: Convolutional Neural Networks for the Adaptive Particle Representation of Large Microscopy Images. Transactions on Machine Learning Research, 2025. [PUMA: convolutional images microscopy networks neural yaff] URL

Maik Fröbe, Andrew Parry, Harrisen Scells, Shuai Wang, Shengyao Zhuang, Guido Zuccon, Martin Potthast, and Matthias Hagen. Corpus Subsampling: Estimating the Effectiveness of Neural Retrieval Models on Large Corpora. Advances in Information Retrieval: 47th European Conference on Information Retrieval, ECIR 2025, Lucca, Italy, April 6–10, 2025, Proceedings, Part I, 453–471, Springer-Verlag, Berlin, Heidelberg, 2025. [PUMA: Evaluation Green IR Retrieval nopdf neural] URL

Chengjin Xu, Fenglong Su, and Jens Lehmann. Time-aware Graph Neural Networks for Entity Alignment between Temporal Knowledge Graphs. 2022. [PUMA: Alignment Entity Graph Knowledge Temporal Time-aware yaff graphs networks neural] URL

Martin Bogdan. Learning algorithms for spiking neural networks: should one use learning algorithms from ANN/DL or neurological plausible learning? - A thought-provoking impulse. XLIII Jornadas de Automática: libro de actas: 7, 8 y 9 de septiembre de 2022, Logroño (La Rioja), 201--207, Servizo de Publicacións da UDC, September 2022. [PUMA: algorithms learning networks neural neurological plausible spiking xack]

Aris Marcolongo, Mykhailo Vladymyrov, Sebastian Lienert, Nadav Peleg, Sigve Haug, and Jakob Zscheischler. Predicting years with extremely low gross primary production from daily weather data using Convolutional Neural Networks. Environmental Data Science, (1):e2, 2022. [PUMA: Convolutional Predicting data gross low primary production weather zno networks neural]