Zobrazeno 1 - 10
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pro vyhledávání: '"Lück, A"'
Autor:
Puliti, Stefano, Lines, Emily R., Müllerová, Jana, Frey, Julian, Schindler, Zoe, Straker, Adrian, Allen, Matthew J., Winiwarter, Lukas, Rehush, Nataliia, Hristova, Hristina, Murray, Brent, Calders, Kim, Terryn, Louise, Coops, Nicholas, Höfle, Bernhard, Junttila, Samuli, Krůček, Martin, Krok, Grzegorz, Král, Kamil, Levick, Shaun R., Luck, Linda, Missarov, Azim, Mokroš, Martin, Owen, Harry J. F., Stereńczak, Krzysztof, Pitkänen, Timo P., Puletti, Nicola, Saarinen, Ninni, Hopkinson, Chris, Torresan, Chiara, Tomelleri, Enrico, Weiser, Hannah, Astrup, Rasmus
Proximally-sensed laser scanning offers significant potential for automated forest data capture, but challenges remain in automatically identifying tree species without additional ground data. Deep learning (DL) shows promise for automation, yet prog
Externí odkaz:
http://arxiv.org/abs/2408.06507
Based on a review of anecdotal beliefs, we explored patterns of track-sequencing within professional music albums. We found that songs with high levels of valence, energy and loudness are more likely to be positioned at the beginning of each album. W
Externí odkaz:
http://arxiv.org/abs/2408.04383
Some imitation learning methods combine behavioural cloning with self-supervision to infer actions from state pairs. However, most rely on a large number of expert trajectories to increase generalisation and human intervention to capture key aspects
Externí odkaz:
http://arxiv.org/abs/2407.04856
This paper studies how a large increase in the price level is transmitted to the real economy through firm balance sheets. Using newly digitized macro- and micro-level data from the German inflation of 1919-1923, we show that inflation led to a large
Externí odkaz:
http://arxiv.org/abs/2405.13296
Imitation learning is an approach in which an agent learns how to execute a task by trying to mimic how one or more teachers perform it. This learning approach offers a compromise between the time it takes to learn a new task and the effort needed to
Externí odkaz:
http://arxiv.org/abs/2404.19456
Autor:
Godrèche, Claude, Luck, Jean-Marc
Convex records have an appealing purely geometric definition. In a sequence of $d$-dimensional data points, the $n$-th point is a convex record if it lies outside the convex hull of all preceding points. We specifically focus on the bivariate (i.e.,
Externí odkaz:
http://arxiv.org/abs/2404.17309
Autor:
Mahamud, Sajid Bin, Butler, Steve, Graff, Hannah, Layman, Nick, Luck, Taylor, Jin, Jiah, Owen, Noah, Yuan, Angela
Coalescing involves gluing one or more rooted graphs onto another graph. Under specific conditions, it is possible to start with cospectral graphs that are coalesced in similar ways that will result in new cospectral graphs. We present a sufficient c
Externí odkaz:
http://arxiv.org/abs/2404.01561
Autor:
Battogtokh, Munkhtulga, Xing, Yiwen, Davidescu, Cosmin, Abdul-Rahman, Alfie, Luck, Michael, Borgo, Rita
In natural language processing (NLP), text classification tasks are increasingly fine-grained, as datasets are fragmented into a larger number of classes that are more difficult to differentiate from one another. As a consequence, the semantic struct
Externí odkaz:
http://arxiv.org/abs/2403.15492
Imitation learning field requires expert data to train agents in a task. Most often, this learning approach suffers from the absence of available data, which results in techniques being tested on its dataset. Creating datasets is a cumbersome process
Externí odkaz:
http://arxiv.org/abs/2403.00550
Autor:
Luck, Jean-Marc
Publikováno v:
Physica A 643 (2024) 129821
This work is inspired by a recent study of a two-dimensional stochastic fragmentation model. We show that the configurational entropy of this model exhibits log-periodic oscillations as a function of the sample size, by exploiting an exact recursion
Externí odkaz:
http://arxiv.org/abs/2403.00432