Search alternatives:
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)
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)
-
1
-
2
-
3
-
4
-
5
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. …”
-
6
-
7
-
8
-
9
Group-level narrow- and broad-band spectral changes after hemispherotomy reveal a marked EEG slowing of the isolated cortex, robust across patients.
Published 2025“…This decrease was larger in the disconnected than in the contralateral cortex. …”
-
10
-
11
Biases in larger populations.
Published 2025“…<p>(<b>A</b>) Maximum absolute bias vs the number of neurons in the population for the Bayesian decoder. …”
-
12
-
13
-
14
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. …”
-
15
-
16
-
17
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. …”
-
18
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. …”
-
19
-
20