Standout Papers

Sigmoid-weighted linear units for neural network function approximation in reinforcement learning 2018 2026 2020 2023 837
  1. Sigmoid-weighted linear units for neural network function approximation in reinforcement learning (2018)
    Stefan Elfwing, Eiji Uchibe et al. Neural Networks
  2. Deep learning, reinforcement learning, and world models (2022)
    Yutaka Matsuo, Yann LeCun et al. Neural Networks

Immediate Impact

4 by Nobel laureates 8 from Science/Nature 58 standout
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Citing Papers

YOLO-MS: Rethinking Multi-Scale Representation Learning for Real-Time Object Detection
2025 Standout
Agentic AI: Autonomous Intelligence for Complex Goals—A Comprehensive Survey
2025 Standout

Works of Eiji Uchibe being referenced

Deep learning, reinforcement learning, and world models
2022 Standout
Sigmoid-weighted linear units for neural network function approximation in reinforcement learning
2018 Standout

Author Peers

Author Last Decade Papers Cites
Eiji Uchibe 567 127 201 460 44 1.6k
Pieter-Tjerk de Boer 486 126 124 501 49 2.0k
Raúl Rojas 467 113 145 353 76 1.7k
Ausif Mahmood 702 74 163 519 50 2.1k
Na Dong 400 133 246 235 96 1.6k
Douglas Creighton 427 62 276 545 60 1.8k
Yaqing Wang 839 54 109 442 54 1.9k
Wenbing Huang 787 88 146 591 61 1.6k
Dawid Połap 930 184 149 602 86 2.1k
Jeremy Wyatt 739 65 317 417 62 1.4k
Marc Parizeau 425 173 99 269 26 1.5k

All Works

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2026