Interpretability of artificial neural network models in artificial intelligence versus neuroscience

被引：24
|
作者：
Kar, Kohitij [1 ,2 ,3 ,4 ]
Kornblith, Simon [5 ]
Fedorenko, Evelina [2 ,3 ]
机构：
[1] York Univ, Ctr Vis Res, Dept Biol, Toronto, ON, Canada
[2] MIT, McGovern Inst Brain Res, Cambridge, MA 02139 USA
[3] MIT, Dept Brain & Cognit Sci, Cambridge, MA 02139 USA
[4] MIT, Ctr Brains Minds & Machines, Cambridge, MA 02139 USA
[5] Brain Team, Google Res, Toronto, ON, Canada
来源：
NATURE MACHINE INTELLIGENCE | 2022年 / 4卷 / 12期
关键词：
D O I：
10.1038/s42256-022-00592-3
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The notion of 'interpretability' of artificial neural networks (ANNs) is of growing importance in neuroscience and artificial intelligence (AI). But interpretability means different things to neuroscientists as opposed to AI researchers. In this article, we discuss the potential synergies and tensions between these two communities in interpreting ANNs.
引用
收藏
页码：1065 / 1067
页数：3
相关论文
共 50 条
  • [31] Study on delay artificial neural network models
    Ma, Ruimin
    Liang, Jiuzhen
    1997, (21):
  • [32] Searching for turbulence models by artificial neural network
    Gamahara, Masataka
    Hattori, Yuji
    PHYSICAL REVIEW FLUIDS, 2017, 2 (05):
  • [33] The analysis of artificial neural network data models
    Roadknight, CM
    Palmer-Brown, D
    Mills, GE
    ADVANCES IN INTELLIGENT DATA ANALYSIS: REASONING ABOUT DATA, 1997, 1280 : 337 - 346
  • [34] Verification and validation of artificial neural network models
    Liu, F
    Yang, M
    AI 2005: ADVANCES IN ARTIFICIAL INTELLIGENCE, 2005, 3809 : 1041 - 1046
  • [35] The analysis and improvement of artificial neural network models
    Zhang, B
    Zhang, L
    1997 IEEE INTERNATIONAL CONFERENCE ON INTELLIGENT PROCESSING SYSTEMS, VOLS 1 & 2, 1997, : 7 - 13
  • [36] ARTIFICIAL NEURAL NETWORK FOR MODELS OF HUMAN OPERATOR
    Ruzek, Martin
    DRIVER-CAR INTERACTION & SAFETY CONFERENCE 2016, 2017, 12 : 99 - 103
  • [37] Real sparks of artificial intelligence and the importance of inner interpretability
    Grzankowski, Alex
    INQUIRY-AN INTERDISCIPLINARY JOURNAL OF PHILOSOPHY, 2024,
  • [38] An artificial neural network model based on neuroscience: Looking closely at the brain
    Rosa, JLG
    ARTIFICIAL NEURAL NETS AND GENETIC ALGORITHMS, 2001, : 138 - 141
  • [39] The brain as artificial intelligence: prospecting the frontiers of neuroscience
    Steve Fuller
    AI & SOCIETY, 2019, 34 : 825 - 833
  • [40] A bibliometric analysis of studies on artificial intelligence in neuroscience
    Tekin, Ugur
    Dener, Murat
    FRONTIERS IN NEUROLOGY, 2025, 16
12345