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Lana Sinapayen
Lana Sinapayen
Associate researcher, Sony CSL
Verified email at csl.sony.co.jp - Homepage
Title
Cited by
Cited by
Year
A strategy for origins of life research
C Scharf, N Virgo, HJ Cleaves, M Aono, N Aubert-Kato, A Aydinoglu, ...
Astrobiology 15 (12), 1031-1042, 2015
602015
Learning by stimulation avoidance: A principle to control spiking neural networks dynamics
L Sinapayen, A Masumori, T Ikegami
PloS one 12 (2), e0170388, 2017
232017
Emergence of sense-making behavior by the Stimulus Avoidance Principle: Experiments on a robot behavior controlled by cultured neuronal cells
A Masumori, N Maruyama, L Sinapayen, T Mita, U Frey, D Bakkum, ...
ECAL 2015: the 13th European Conference on Artificial Life, 373-380, 2015
92015
Neural autopoiesis: Organizing self-boundaries by stimulus avoidance in biological and artificial neural networks
A Masumori, L Sinapayen, N Maruyama, T Mita, D Bakkum, U Frey, ...
Artificial Life 26 (1), 130-151, 2020
62020
Learning by stimulation avoidance scales to large neural networks
A Masumori, L Sinapayen, T Ikegami
ECAL 2017, the Fourteenth European Conference on Artificial Life, 275-282, 2017
62017
Sound processing device, sound processing method, and sound processing program
K Nakadai, K Nakamura, L Sinapayen, M Imai
US Patent 9,664,772, 2017
52017
Interactive sound source localization using robot audition for tablet devices
K Nakamura, L Sinapayen, K Nakadai
2015 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2015
52015
Learning by Stimulation Avoidance as a primary principle of spiking neural networks dynamics
L Sinapayen, A Masumori, N Virgo, T Ikegami
ECAL 2015: the 13th European Conference on Artificial Life, 175-182, 2015
52015
Consensus-based sound source localization using a swarm of micro-quadrocopters
S Lana, K Takahashi, T Kinoshita
Proc. Robot. Soc. Japan, Tokyo, Japan, 1-4, 2015
52015
Reactive, proactive, and inductive agents: an evolutionary path for biological and artificial spiking networks
L Sinapayen, A Masumori, T Ikegami
Frontiers in computational neuroscience 13, 88, 2020
42020
Predictive coding as stimulus avoidance in spiking neural networks
A Masumori, T Ikegami, L Sinapayen
2019 IEEE Symposium Series on Computational Intelligence (SSCI), 271-277, 2019
42019
Assessing planetary complexity and potential agnostic biosignatures using epsilon machines
S Bartlett, J Li, L Gu, L Sinapayen, S Fan, V Natraj, JH Jiang, D Crisp, ...
Nature Astronomy 6 (3), 387-392, 2022
32022
Autonomous regulation of self and non-self by stimulation avoidance in embodied neural networks
A Masumori, L Sinapayen, N Maruyama, T Mita, D Bakkum, U Frey, ...
ALIFE 2018: The 2018 Conference on Artificial Life, 163-170, 2018
32018
Online fitting of computational cost to environmental complexity: predictive coding with the ε-network
L Sinapayen, T Ikegami
ECAL 2017, the Fourteenth European Conference on Artificial Life, 380-387, 2017
32017
Swarm of micro-quadrocopters for consensus-based sound source localization
L Sinapayen, K Nakamura, K Nakadai, H Takahashi, T Kinoshita
Advanced Robotics 31 (12), 624-633, 2017
22017
Evolutionary generation of visual motion illusions
L Sinapayen, E Watanabe
arXiv preprint arXiv:2112.13243, 2021
12021
Perspective: Purposeful Failure in Artificial Life and Artificial Intelligence
L Sinapayen
arXiv preprint arXiv:2102.12076, 2021
12021
DNN Architecture for High Performance Prediction on Natural Videos Loses Submodule's Ability to Learn Discrete-World Dataset
L Sinapayen, A Noda
arXiv preprint arXiv:1904.07969, 2019
12019
Multicopter localization using sound landmarks
L Sinapayen, K Nakamura, K Nakadai, H Takahashi, T Kinoshita
情報処理学会第 76 回全国大会 3, 8, 2014
12014
Quantifying Planetary Complexity and Potential Agnostic Biosignatures using Epsilon Machines
S Bartlett, J Li, L Gu, L Sinapayen, S Fan, V Natraj, JH Jiang, D Crisp, ...
2022 Astrobiology Science Conference, 2022
2022
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