Search alternatives:
latest decrease » largest decrease (Expand Search), greatest decrease (Expand Search), largest decreases (Expand Search)
marked decrease » marked increase (Expand Search)
task decrease » a decrease (Expand Search), ash decreased (Expand Search)
teer decrease » mean decrease (Expand Search), greater decrease (Expand Search)
latest decrease » largest decrease (Expand Search), greatest decrease (Expand Search), largest decreases (Expand Search)
marked decrease » marked increase (Expand Search)
task decrease » a decrease (Expand Search), ash decreased (Expand Search)
teer decrease » mean decrease (Expand Search), greater decrease (Expand Search)
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ROC analysis to mark selectivity results in mostly mixed-selective units.
Published 2025“…The large number of mixed selective units also results in a significant decrease in accuracy when these neurons are targeted as compared to <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1013559#pcbi.1013559.g006" target="_blank">Fig 6c</a> where there was no significant effect visible after targeting mixed selective units, likely because there were less mixed selective units present. …”
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Network architectures for multi-agents task.
Published 2025“…<div><p>Deep reinforcement learning has achieved significant success in complex decision-making tasks. However, the high computational cost of policies based on deep neural networks restricts their practical application. …”
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Time(s) and GFLOPs savings of single-agent tasks.
Published 2025“…<div><p>Deep reinforcement learning has achieved significant success in complex decision-making tasks. However, the high computational cost of policies based on deep neural networks restricts their practical application. …”
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Scores vs Skip ratios on single-agent task.
Published 2025“…<div><p>Deep reinforcement learning has achieved significant success in complex decision-making tasks. However, the high computational cost of policies based on deep neural networks restricts their practical application. …”
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Win rate vs Skip ratios on multi-agents tasks.
Published 2025“…<div><p>Deep reinforcement learning has achieved significant success in complex decision-making tasks. However, the high computational cost of policies based on deep neural networks restricts their practical application. …”