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pro vyhledávání: '"A Meulemans"'
We study the visual complexity of animated transitions between point sets. Although there exist many metrics for point set similarity, these metrics are not adequate for this purpose, as they typically treat each point separately. Instead, we propose
Externí odkaz:
http://arxiv.org/abs/2411.17920
Autor:
Meulemans, Alexander, Kobayashi, Seijin, von Oswald, Johannes, Scherrer, Nino, Elmoznino, Eric, Richards, Blake, Lajoie, Guillaume, Arcas, Blaise Agüera y, Sacramento, João
Self-interested individuals often fail to cooperate, posing a fundamental challenge for multi-agent learning. How can we achieve cooperation among self-interested, independent learning agents? Promising recent work has shown that in certain tasks coo
Externí odkaz:
http://arxiv.org/abs/2410.18636
Points of interest on a map such as restaurants, hotels, or subway stations, give rise to categorical point data: data that have a fixed location and one or more categorical attributes. Consequently, recent years have seen various set visualization a
Externí odkaz:
http://arxiv.org/abs/2407.14433
Constructing partitions of colored points is a well-studied problem in discrete and computational geometry. We study the problem of creating a minimum-cardinality partition into monochromatic islands. Our input is a set $S$ of $n$ points in the plane
Externí odkaz:
http://arxiv.org/abs/2402.13340
Autor:
Wu, Haolun, Yuan, Ye, Mikaelyan, Liana, Meulemans, Alexander, Liu, Xue, Hensman, James, Mitra, Bhaskar
Recent advances in machine learning have significantly impacted the field of information extraction, with Language Models (LMs) playing a pivotal role in extracting structured information from unstructured text. Prior works typically represent inform
Externí odkaz:
http://arxiv.org/abs/2402.04437
Autor:
Gärtner, Bernd, Kalani, Vishwas, Reddy, Meghana M., Meulemans, Wouter, Speckmann, Bettina, Stojaković, Miloš
In information visualization, the position of symbols often encodes associated data values. When visualizing data elements with both a numerical and a categorical dimension, positioning in the categorical axis admits some flexibility. This flexibilit
Externí odkaz:
http://arxiv.org/abs/2310.01147
Autor:
von Oswald, Johannes, Schlegel, Maximilian, Meulemans, Alexander, Kobayashi, Seijin, Niklasson, Eyvind, Zucchet, Nicolas, Scherrer, Nino, Miller, Nolan, Sandler, Mark, Arcas, Blaise Agüera y, Vladymyrov, Max, Pascanu, Razvan, Sacramento, João
Some autoregressive models exhibit in-context learning capabilities: being able to learn as an input sequence is processed, without undergoing any parameter changes, and without being explicitly trained to do so. The origins of this phenomenon are st
Externí odkaz:
http://arxiv.org/abs/2309.05858
Would I have gotten that reward? Long-term credit assignment by counterfactual contribution analysis
To make reinforcement learning more sample efficient, we need better credit assignment methods that measure an action's influence on future rewards. Building upon Hindsight Credit Assignment (HCA), we introduce Counterfactual Contribution Analysis (C
Externí odkaz:
http://arxiv.org/abs/2306.16803
Autor:
Meulemans, Marie, Durocher, Antoine, Versailles, Philippe, Bourque, Gilles, Bergthorson, Jeffrey M.
Publikováno v:
In Journal of Quantitative Spectroscopy and Radiative Transfer January 2025 330
Autor:
Meulemans, Alexander, Zucchet, Nicolas, Kobayashi, Seijin, von Oswald, Johannes, Sacramento, João
Equilibrium systems are a powerful way to express neural computations. As special cases, they include models of great current interest in both neuroscience and machine learning, such as deep neural networks, equilibrium recurrent neural networks, dee
Externí odkaz:
http://arxiv.org/abs/2207.01332