47 citations · 94 across the 21 of their papers we have counts for
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cs.LG2023
Loss- and Reward-Weighting for Efficient Distributed Reinforcement Learning
Martin Holen, Per-Arne Andersen, Kristian Muri Knausgård +1
This paper introduces two learning schemes for distributed agents in Reinforcement Learning (RL) environments, namely Reward-Weighted (R-Weighted) and Loss-Weighted (L-Weighted) gr…
cs.CV2023★ 1 cited
A contrastive learning approach for individual re-identification in a wild fish population
Ørjan Langøy Olsen, Tonje Knutsen Sørdalen, Morten Goodwin +3
In both terrestrial and marine ecology, physical tagging is a frequently used method to study population dynamics and behavior. However, such tagging techniques are increasingly be…