Michael Beyeler
Citado por
Citado por
Categorization and decision-making in a neurobiologically plausible spiking network using a STDP-like learning rule
M Beyeler, ND Dutt, JL Krichmar
Neural Networks 48, 109-124, 2013
CARLsim 4: An open source library for large scale, biologically detailed spiking neural network simulation using heterogeneous clusters
TS Chou, HJ Kashyap, J Xing, S Listopad, EL Rounds, M Beyeler, N Dutt, ...
2018 International joint conference on neural networks (IJCNN), 1-8, 2018
A model of ganglion axon pathways accounts for percepts elicited by retinal implants
M Beyeler, D Nanduri, JD Weiland, A Rokem, GM Boynton, I Fine
Scientific Reports 9 (1), 1-16, 2019
Learning to see again: biological constraints on cortical plasticity and the implications for sight restoration technologies
M Beyeler, A Rokem, GM Boynton, I Fine
Journal of Neural Engineering 14 (5), 051003, 2017
Neural correlates of sparse coding and dimensionality reduction
M Beyeler, EL Rounds, KD Carlson, N Dutt, JL Krichmar
PLoS computational biology 15 (6), e1006908, 2019
CARLsim 3: A user-friendly and highly optimized library for the creation of neurobiologically detailed spiking neural networks
M Beyeler, KD Carlson, TS Chou, N Dutt, JL Krichmar
2015 International Joint Conference on Neural Networks (IJCNN), 1-8, 2015
Vision-based robust road lane detection in urban environments
M Beyeler, F Mirus, A Verl
2014 IEEE International Conference on Robotics and Automation (ICRA), 4920-4925, 2014
Machine Learning for OpenCV
M Beyeler
Packt Publishing Ltd, 2017
pulse2percept: A Python-based simulation framework for bionic vision
M Beyeler, GM Boynton, I Fine, A Rokem
2017 Scientific Computing with Python (SciPy) Conference, 2017
A GPU-accelerated cortical neural network model for visually guided robot navigation
M Beyeler, N Oros, N Dutt, JL Krichmar
Neural Networks 72, 75-87, 2015
OpenCV: Computer Vision Projects with Python
J Howse, P Joshi, M Beyeler
Packt Publishing Ltd, 2016
OpenCV with Python Blueprints
M Beyeler
Packt Publishing Ltd, 2015
3D visual response properties of MSTd emerge from an efficient, sparse population code
M Beyeler, N Dutt, JL Krichmar
Journal of Neuroscience 36 (32), 8399-8415, 2016
Deep Learning–Based Scene Simplification for Bionic Vision
N Han, S Srivastava, A Xu, D Klein, M Beyeler
AHs'21: Augmented Humans Conference 2021, 45-54, 2021
Efficient spiking neural network model of pattern motion selectivity in visual cortex
M Beyeler, M Richert, ND Dutt, JL Krichmar
Neuroinformatics 12, 435-454, 2014
Data-driven models in human neuroscience and neuroengineering
BW Brunton, M Beyeler
Current Opinion in Neurobiology 58, 21-29, 2019
Exploring olfactory sensory networks: simulations and hardware emulation
M Beyeler, F Stefanini, H Proske, G Galizia, E Chicca
2010 Biomedical Circuits and Systems Conference (BioCAS), 270-273, 2010
GPGPU accelerated simulation and parameter tuning for neuromorphic applications
KD Carlson, M Beyeler, N Dutt, JL Krichmar
2014 19th Asia and South Pacific Design Automation Conference (ASP-DAC), 570-577, 2014
Machine Learning for OpenCV 4 - Second Edition
A Sharma, VR Shrimali, M Beyeler
Packt Publishing Ltd., 2019
Sparse and efficient neuromorphic population coding
M Beyeler, ND Dutt, JL Krichmar
US Patent App. 15/417,626, 2017
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