E. O. Neftci,
H. Mostafa, and
F. Zenke

Surrogate Gradient Learning in Spiking Neural Networks

*arXiv preprint arXiv:1901.09948,
2019
*

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Surrogate Gradient Learning in Spiking Neural Networks

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E. Neftci and
B. Averbeck

Reinforcement Learning in Artificial and Biological Systems

*Nature Machine Intelligence ((Accepted)),
2019
*

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Reinforcement Learning in Artificial and Biological Systems

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E. O. Neftci

**Data and Power Efficient Intelligence with Neuromorphic Learning Machines**

*iScience,
***5**,
2018

systems neuroscience computer science evolvable hardware

URL, DOI, RIS, BibTex

systems neuroscience computer science evolvable hardware

URL, DOI, RIS, BibTex

J. Kaiser,
H. Mostafa, and
E. Neftci

Synaptic Plasticity for Deep Continuous Local Learning

*arXiv preprint arXiv:1812.10766,
2018
*

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Synaptic Plasticity for Deep Continuous Local Learning

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M. E. Fouda,
E. Neftci,
A. Eltawil, and
F. Kurdahi

Independent Component Analysis using RRAMs

*IEEE Transactions on Nanotechnology ((accepted)),
2018
*

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Independent Component Analysis using RRAMs

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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**

*Frontiers in Neuroscience,
***12**,
2018

URL, DOI, RIS, BibTex

URL, DOI, RIS, BibTex

G. Detorakis,
T. Bartley, and
E. Neftci

**Contrastive Hebbian Learning with Random Feedback Weights**

*Neural Networks ((accepted)),
2018
*

URL, RIS, BibTex

URL, RIS, BibTex

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

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

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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

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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

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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

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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

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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

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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

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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

H. J. Kashyap,
G. Detorakis,
N. Dutt,
J. L. Krichmar, and
E. Neftci

A Recurrent Neural Network Based Model of Predictive Smooth Pursuit Eye Movement in Primates

*2018 International Joint Conference on Neural Networks (IJCNN),
2018*

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A Recurrent Neural Network Based Model of Predictive Smooth Pursuit Eye Movement in Primates

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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

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E. Neftci

Stochastic synapses as resource for efficient deep learning machines

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

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Stochastic synapses as resource for efficient deep learning machines

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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,
2016*

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

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P. U. Diehl,
B. U. Pedroni,
A. 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

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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

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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

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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

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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

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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*

DOI, ISBN, RIS, BibTex

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

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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

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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

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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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