E. O. Neftci,
C. Augustine,
S. Paul, and
G. Detorakis

Event-Driven Random Back-Propagation: Enabling Neuromorphic Deep Learning Machines

*Frontiers in Neuroscience,
***11**,
2017

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Event-Driven Random Back-Propagation: Enabling Neuromorphic Deep Learning Machines

DOI, RIS, BibTex

G. Detorakis,
S. Sheik,
C. Augustine,
S. Paul,
B. U. Pedroni,
N. Dutt,
J. Krichmar,
G. Cauwenberghs,
*et al.*

Neural and Synaptic Array Transceiver: A Brain-Inspired Computing Framework for Embedded Learning

*arXiv preprint arXiv:1709.10205,
2017
*

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Neural and Synaptic Array Transceiver: A Brain-Inspired Computing Framework for Embedded Learning

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S. B. Eryilmaz,
E. Neftci,
S. Joshi,
S. Kim,
M. BrightSky,
H. L. Lung,
C. Lam,
G. Cauwenberghs,
*et al.*

Training a Probabilistic Graphical Model With Resistive Switching Electronic Synapses

*IEEE Transactions on Electron Devices,
***63**(12),
2016

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Training a Probabilistic Graphical Model With Resistive Switching Electronic Synapses

DOI, RIS, BibTex

E. O. Neftci,
B. U. Pedroni,
S. Joshi,
M. Al-Shedivat, and
G. Cauwenberghs

Stochastic Synapses Enable Efficient Brain-Inspired Learning Machines

*Frontiers in Neuroscience,
***10**(241),
2016

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Stochastic Synapses Enable Efficient Brain-Inspired Learning Machines

DOI, RIS, BibTex

R. Naous,
M. AlShedivat,
E. Neftci,
G. Cauwenberghs, and
K. N. Salama

Memristor-based neural networks: Synaptic versus neuronal stochasticity

*Aip Advances,
***6**(11),
2016

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Memristor-based neural networks: Synaptic versus neuronal stochasticity

RIS, BibTex

J. Fonollosa,
E. Neftci, and
M. Rabinovich

Learning of Chunking Sequences in Cognition and Behavior.

*PLoS computational biology ((equal contrib. JF, EN)),
***11**(11),
2015

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Learning of Chunking Sequences in Cognition and Behavior.

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F. Stefanini,
E. Neftci,
S. Sheik, and
G. Indiveri

PyNCS: a kernel for high-level configuration and definition of neuromorphic electronic systems

*Frontiers in Neuroinformatics ((equal contrib. FS, EN, SS)),
***8**,
2014

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PyNCS: a kernel for high-level configuration and definition of neuromorphic electronic systems

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E. Neftci,
S. Das,
B. Pedroni,
K. Kreutz-Delgado, and
G. Cauwenberghs

Event-Driven Contrastive Divergence for Spiking Neuromorphic Systems

*Frontiers in Neuroscience,
***7**(272),
2014

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Event-Driven Contrastive Divergence for Spiking Neuromorphic Systems

DOI, RIS, BibTex

E. Neftci,
J. Binas,
U. Rutishauser,
E. Chicca,
G. Indiveri, and
R. J. Douglas

Synthesizing cognition in neuromorphic electronic systems

*PNAS,
***110**(37),
2013

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Synthesizing cognition in neuromorphic electronic systems

RIS, BibTex

A. Landsman,
E. Neftci, and
D. Muir

Noise robustness and spatially patterned synchronization of cortical oscillators

*New Journal of Physics ((equal contrib. AL, EN, DM)),
***14**(12),
2012

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Noise robustness and spatially patterned synchronization of cortical oscillators

RIS, BibTex

E. Neftci,
B. Toth,
G. Indiveri, and
H. Abarbanel

Dynamic State and Parameter Estimation applied to Neuromorphic Systems

*Neural Computation,
***24**(7),
2012

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Dynamic State and Parameter Estimation applied to Neuromorphic Systems

DOI, RIS, BibTex

E. Neftci,
E. Chicca,
G. Indiveri, and
R. Douglas

A systematic method for configuring VLSI networks of spiking neurons

*Neural Computation,
***23**(10),
2011

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A systematic method for configuring VLSI networks of spiking neurons

DOI, RIS, BibTex

E. Neftci,
C. Augustine,
S. Paul, and
G. Detorakis

Event-driven Random Back-Propagation: Enabling Neuromorphic Deep Learning Machines

*2017 IEEE International Symposium on Circuits and Systems,
2017*

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Event-driven Random Back-Propagation: Enabling Neuromorphic Deep Learning Machines

RIS, BibTex

E. Neftci

Stochastic Synapses as Resource for Efficient Deep Learning Machines

*2017 IEEE International Electron Devices Meeting (IEDM) ((in press)),
2017*

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Stochastic Synapses as Resource for Efficient Deep Learning Machines

RIS, BibTex

B. U. Pedroni,
S. Sheik,
S. Joshi,
G. Detorakis,
S. Paul,
C. Augustine,
E. Neftci, and
G. Cauwenberghs

Forward Table-Based Presynaptic Event-Triggered Spike-Timing-Dependent Plasticity

*
2016*

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Forward Table-Based Presynaptic Event-Triggered Spike-Timing-Dependent Plasticity

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P. U. Diehl,
G. Zarrella,
A. Cassidy,
B. Pedroni, and
E. Neftci

Conversion of Artificial Recurrent Neural Networks to Spiking Neural Networks for Low-power Neuromorphic Hardware

*International Conference on Rebooting Computation (ICRC), 2016 ((accepted at ICRC 2016)),
2016*

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Conversion of Artificial Recurrent Neural Networks to Spiking Neural Networks for Low-power Neuromorphic Hardware

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A. D. P. U. P. B. U. Cassidy,
P. Merolla,
E. Neftci, and
G. Zarrella

TrueHappiness: Neuromorphic Emotion Recognition on TrueNorth

*arXiv:1601.04183,
2016
*

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TrueHappiness: Neuromorphic Emotion Recognition on TrueNorth

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S. Sheik,
S. Paul,
C. Augustine,
C. Kothapalli,
G. Cauwenberghs, and
E. Neftci

Synaptic sampling in hardware spiking neural networks

*International Symposium on Circuits and Systems, ({ISCAS}), 2016,
2016*

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Synaptic sampling in hardware spiking neural networks

RIS, BibTex

S. B. Eryilmaz,
S. Joshi,
E. Neftci,
W. Wan,
G. Cauwenberghs, and
H.-S. P. Wong

Neuromorphic Architectures with Electronic Synapses

*International Symposium on Quality Electronic Design (ISQED),
2016*

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Neuromorphic Architectures with Electronic Synapses

RIS, BibTex

R. Naous,
M. Al-Shedivat,
E. Neftci,
G. Cauwenberghs, and
K. N. Salama

Stochastic synaptic plasticity with memristor crossbar arrays

*Circuits and Systems (ISCAS), 2016 IEEE International Symposium on,
2016*

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Stochastic synaptic plasticity with memristor crossbar arrays

RIS, BibTex

M. Al-Shedivat,
E. Neftci, and
G. Cauwenberghs

Neural generative models with stochastic synapses capture richer representations

*Cosyne Abstracts,
2015*

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Neural generative models with stochastic synapses capture richer representations

RIS, BibTex

M. Al-Shedivat,
E. Neftci, and
G. Cauwenberghs

Learning Non-deterministic Representations with Energy-based Ensembles

*arXiv preprint arXiv:1412.7272,
2015
*

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Learning Non-deterministic Representations with Energy-based Ensembles

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M. Al-Shedivat,
R. Naous,
E. Neftci,
G. Cauwenberghs, and
K. Salama

Inherently Stochastic Spiking Neurons for Probabilistic Neural Computation

*IEEE EMBS Conference on Neural Engineering,
2015*

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Inherently Stochastic Spiking Neurons for Probabilistic Neural Computation

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J. Park,
S. Ha,
T. Yu,
E. Neftci, and
G. Cauwenberghs

A 65k-Neuron 73-Mevents/S 22-pJ/Event Asynchronous Micro-Pipelined Integrate-and-Fire Array Transceiver

*Biomedical Circuits and Systems Conference ({BioCAS}),
2014*

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A 65k-Neuron 73-Mevents/S 22-pJ/Event Asynchronous Micro-Pipelined Integrate-and-Fire Array Transceiver

RIS, BibTex

D. Corneil,
E. Neftci,
G. Indiveri, and
M. Pfeiffer

Learning, Inference, and Replay of Hidden State Sequences in Recurrent Spiking Neural Networks

*Cosyne Abstracts,
2014*

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Learning, Inference, and Replay of Hidden State Sequences in Recurrent Spiking Neural Networks

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B. Pedroni,
S. Das,
E. Neftci,
K. Kreutz-Delgado, and
G. Cauwenberghs

Neuromorphic Adaptations of Restricted Boltzmann Machines and Deep Belief Networks

*International Joint Conference on Neural Networks, {IJCNN} 2013,
2013*

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Neuromorphic Adaptations of Restricted Boltzmann Machines and Deep Belief Networks

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E. Neftci,
J. Binas,
E. Chicca,
G. Indiveri, and
R. Douglas

Systematic Construction of Finite State Automata Using VLSI Spiking Neurons

*Biomimetic and Biohybrid Systems,
Springer Berlin / Heidelberg,
2012,
ISBN 978-3-642-31524-4*

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Systematic Construction of Finite State Automata Using VLSI Spiking Neurons

DOI, ISBN, RIS, BibTex

D. Corneil,
D. Sonnleithner,
E. Neftci,
E. Chicca,
M. Cook,
G. Indiveri, and
R. Douglas

Real-time inference in a VLSI spiking neural network

*International Symposium on Circuits and Systems, ({ISCAS}), 2012,
2012*

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Real-time inference in a VLSI spiking neural network

DOI, RIS, BibTex

D. Corneil,
D. Sonnleithner,
E. Neftci,
E. Chicca,
M. Cook,
G. Indiveri, and
R. Douglas

Function approximation with uncertainty propagation in a VLSI spiking neural network

*International Joint Conference on Neural Networks, {(IJCNN)} 2012,
2012*

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Function approximation with uncertainty propagation in a VLSI spiking neural network

DOI, RIS, BibTex

S. Sheik,
F. Stefanini,
E. Neftci,
E. Chicca, and
G. Indiveri

Systematic configuration and automatic tuning of neuromorphic systems

*International Symposium on Circuits and Systems, ({ISCAS}), 2011,
2011*

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Systematic configuration and automatic tuning of neuromorphic systems

DOI, RIS, BibTex

E. Neftci,
E. Chicca,
M. Cook,
G. Indiveri, and
R. Douglas

State-Dependent Sensory Processing in Networks of VLSI Spiking Neurons

*International Symposium on Circuits and Systems, ({ISCAS}), 2010,
2010*

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State-Dependent Sensory Processing in Networks of VLSI Spiking Neurons

DOI, RIS, BibTex

E. Neftci and
G. Indiveri

A Device Mismatch Compensation Method for VLSI Spiking Neural Networks

*Biomedical Circuits and Systems Conference ({BioCAS}), 2010,
2010*

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A Device Mismatch Compensation Method for VLSI Spiking Neural Networks

DOI, RIS, BibTex

E. Neftci,
E. Chicca,
G. Indiveri,
J.-J. Slotine, and
R. Douglas

Contraction Properties of VLSI Cooperative Competitive Neural Networks of Spiking Neurons

*Advances in Neural Information Processing Systems (NIPS),
MIT Press,
2008*

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Contraction Properties of VLSI Cooperative Competitive Neural Networks of Spiking Neurons

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E. Neftci,
S. Das,
B. Pedroni,
K. Kreutz-Delgado, and
G. Cauwenberghs

Restricted Boltzmann Machines and Continuous-time Contrastive Divergence in Spiking Neuromorphic Systems

*20th Joint Symposium on Neural Computation,
2013*

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Restricted Boltzmann Machines and Continuous-time Contrastive Divergence in Spiking Neuromorphic Systems

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