Skip to content

Commit 419ef83

Browse files
akorgorakorgor
committed
Update reference
1 parent 619d3f4 commit 419ef83

21 files changed

+89
-70
lines changed

‎models/eprop_iaf.h‎

Lines changed: 5 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -302,9 +302,10 @@ References
302302
networks of spiking neurons. Nature Communications, 11:3625.
303303
https://doi.org/10.1038/s41467-020-17236-y
304304
305-
.. [2] Korcsak-Gorzo A, Stapmanns J, Espinoza Valverde JA, Plesser HE,
306-
Dahmen D, Bolten M, Van Albada SJ, Diesmann M. Event-based
307-
implementation of eligibility propagation (in preparation)
305+
.. [2] Korcsak-Gorzo A, Espinoza Valverde JA, Stapmanns J, Plesser HE, Dahmen D,
306+
Bolten M, van Albada SJ, Diesmann M (2025). Event-driven eligibility
307+
propagation in large sparse networks: efficiency shaped by biological
308+
realism. arXiv:2511.21674. https://doi.org/10.48550/arXiv.2511.21674
308309
309310
.. start_surrogate-gradient-references
310311
@@ -354,7 +355,7 @@ void register_eprop_iaf( const std::string& name );
354355
*
355356
* Class implementing a current-based leaky integrate-and-fire neuron model with delta-shaped postsynaptic currents for
356357
* e-prop plasticity according to Bellec et al. (2020) with additional biological features described in
357-
* Korcsak-Gorzo, Stapmanns, and Espinoza Valverde et al. (in preparation).
358+
* Korcsak-Gorzo et al. (2025).
358359
*/
359360
class eprop_iaf : public EpropArchivingNodeRecurrent< false >
360361
{

‎models/eprop_iaf_adapt.h‎

Lines changed: 5 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -287,9 +287,10 @@ References
287287
networks of spiking neurons. Nature Communications, 11:3625.
288288
https://doi.org/10.1038/s41467-020-17236-y
289289
290-
.. [2] Korcsak-Gorzo A, Stapmanns J, Espinoza Valverde JA, Plesser HE,
291-
Dahmen D, Bolten M, Van Albada SJ, Diesmann M. Event-based
292-
implementation of eligibility propagation (in preparation)
290+
.. [2] Korcsak-Gorzo A, Espinoza Valverde JA, Stapmanns J, Plesser HE, Dahmen D,
291+
Bolten M, van Albada SJ, Diesmann M (2025). Event-driven eligibility
292+
propagation in large sparse networks: efficiency shaped by biological
293+
realism. arXiv:2511.21674. https://doi.org/10.48550/arXiv.2511.21674
293294
294295
.. include:: ../models/eprop_iaf.rst
295296
:start-after: .. start_surrogate-gradient-references
@@ -322,7 +323,7 @@ void register_eprop_iaf_adapt( const std::string& name );
322323
*
323324
* Class implementing a current-based leaky integrate-and-fire neuron model with delta-shaped postsynaptic currents and
324325
* threshold adaptation for e-prop plasticity according to Bellec et al. (2020) with additional biological features
325-
* described in Korcsak-Gorzo, Stapmanns, and Espinoza Valverde et al. (in preparation).
326+
* described in Korcsak-Gorzo et al. (2025).
326327
*/
327328
class eprop_iaf_adapt : public EpropArchivingNodeRecurrent< false >
328329
{

‎models/eprop_iaf_adapt_bsshslm_2020.h‎

Lines changed: 4 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -258,9 +258,10 @@ References
258258
networks of spiking neurons. Nature Communications, 11:3625.
259259
https://doi.org/10.1038/s41467-020-17236-y
260260
261-
.. [2] Korcsak-Gorzo A, Stapmanns J, Espinoza Valverde JA, Plesser HE,
262-
Dahmen D, Bolten M, Van Albada SJ, Diesmann M. Event-based
263-
implementation of eligibility propagation (in preparation)
261+
.. [2] Korcsak-Gorzo A, Espinoza Valverde JA, Stapmanns J, Plesser HE, Dahmen D,
262+
Bolten M, van Albada SJ, Diesmann M (2025). Event-driven eligibility
263+
propagation in large sparse networks: efficiency shaped by biological
264+
realism. arXiv:2511.21674. https://doi.org/10.48550/arXiv.2511.21674
264265
265266
.. include:: ../models/eprop_iaf.rst
266267
:start-after: .. start_surrogate-gradient-references

‎models/eprop_iaf_bsshslm_2020.h‎

Lines changed: 4 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -242,9 +242,10 @@ References
242242
networks of spiking neurons. Nature Communications, 11:3625.
243243
https://doi.org/10.1038/s41467-020-17236-y
244244
245-
.. [2] Korcsak-Gorzo A, Stapmanns J, Espinoza Valverde JA, Plesser HE,
246-
Dahmen D, Bolten M, Van Albada SJ, Diesmann M. Event-based
247-
implementation of eligibility propagation (in preparation)
245+
.. [2] Korcsak-Gorzo A, Espinoza Valverde JA, Stapmanns J, Plesser HE, Dahmen D,
246+
Bolten M, van Albada SJ, Diesmann M (2025). Event-driven eligibility
247+
propagation in large sparse networks: efficiency shaped by biological
248+
realism. arXiv:2511.21674. https://doi.org/10.48550/arXiv.2511.21674
248249
249250
.. include:: ../models/eprop_iaf.rst
250251
:start-after: .. start_surrogate-gradient-references

‎models/eprop_iaf_psc_delta.h‎

Lines changed: 5 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -308,9 +308,10 @@ References
308308
networks of spiking neurons. Nature Communications, 11:3625.
309309
https://doi.org/10.1038/s41467-020-17236-y
310310
311-
.. [2] Korcsak-Gorzo A, Stapmanns J, Espinoza Valverde JA, Plesser HE,
312-
Dahmen D, Bolten M, Van Albada SJ, Diesmann M. Event-based
313-
implementation of eligibility propagation (in preparation)
311+
.. [2] Korcsak-Gorzo A, Espinoza Valverde JA, Stapmanns J, Plesser HE, Dahmen D,
312+
Bolten M, van Albada SJ, Diesmann M (2025). Event-driven eligibility
313+
propagation in large sparse networks: efficiency shaped by biological
314+
realism. arXiv:2511.21674. https://doi.org/10.48550/arXiv.2511.21674
314315
315316
.. [3] Neftci EO, Mostafa H, Zenke F (2019). Surrogate Gradient Learning in
316317
Spiking Neural Networks. IEEE Signal Processing Magazine, 36(6), 51-63.
@@ -366,7 +367,7 @@ void register_eprop_iaf_psc_delta( const std::string& name );
366367
*
367368
* Class implementing a current-based leaky integrate-and-fire neuron model with delta-shaped postsynaptic currents for
368369
* e-prop plasticity according to Bellec et al. (2020) with additional biological features described in
369-
* Korcsak-Gorzo, Stapmanns, and Espinoza Valverde et al. (in preparation).
370+
* Korcsak-Gorzo et al. (2025).
370371
*/
371372
class eprop_iaf_psc_delta : public EpropArchivingNodeRecurrent< false >
372373
{

‎models/eprop_iaf_psc_delta_adapt.h‎

Lines changed: 5 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -323,9 +323,10 @@ References
323323
networks of spiking neurons. Nature Communications, 11:3625.
324324
https://doi.org/10.1038/s41467-020-17236-y
325325
326-
.. [2] Korcsak-Gorzo A, Stapmanns J, Espinoza Valverde JA, Plesser HE,
327-
Dahmen D, Bolten M, Van Albada SJ, Diesmann M. Event-based
328-
implementation of eligibility propagation (in preparation)
326+
.. [2] Korcsak-Gorzo A, Espinoza Valverde JA, Stapmanns J, Plesser HE, Dahmen D,
327+
Bolten M, van Albada SJ, Diesmann M (2025). Event-driven eligibility
328+
propagation in large sparse networks: efficiency shaped by biological
329+
realism. arXiv:2511.21674. https://doi.org/10.48550/arXiv.2511.21674
329330
330331
.. [3] Neftci EO, Mostafa H, Zenke F (2019). Surrogate Gradient Learning in
331332
Spiking Neural Networks. IEEE Signal Processing Magazine, 36(6), 51-63.
@@ -382,7 +383,7 @@ void register_eprop_iaf_psc_delta_adapt( const std::string& name );
382383
*
383384
* Class implementing a current-based leaky integrate-and-fire neuron model with delta-shaped postsynaptic currents
384385
* and spike threshold adaptation for e-prop plasticity according to Bellec et al. (2020) with additional biological
385-
* features described in Korcsak-Gorzo, Stapmanns, and Espinoza Valverde et al. (in preparation).
386+
* features described in Korcsak-Gorzo et al. (2025).
386387
*/
387388
class eprop_iaf_psc_delta_adapt : public EpropArchivingNodeRecurrent< false >
388389
{

‎models/eprop_learning_signal_connection.h‎

Lines changed: 5 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -106,9 +106,10 @@ References
106106
networks of spiking neurons. Nature Communications, 11:3625.
107107
https://doi.org/10.1038/s41467-020-17236-y
108108
109-
.. [2] Korcsak-Gorzo A, Stapmanns J, Espinoza Valverde JA, Plesser HE,
110-
Dahmen D, Bolten M, Van Albada SJ, Diesmann M. Event-based
111-
implementation of eligibility propagation (in preparation)
109+
.. [2] Korcsak-Gorzo A, Espinoza Valverde JA, Stapmanns J, Plesser HE, Dahmen D,
110+
Bolten M, van Albada SJ, Diesmann M (2025). Event-driven eligibility
111+
propagation in large sparse networks: efficiency shaped by biological
112+
realism. arXiv:2511.21674. https://doi.org/10.48550/arXiv.2511.21674
112113
113114
See also
114115
++++++++
@@ -127,7 +128,7 @@ void register_eprop_learning_signal_connection( const std::string& name );
127128
*
128129
* Class implementing a synapse model transmitting secondary feedback learning signals for e-prop plasticity
129130
* according to Bellec et al. (2020) with additional biological features described in
130-
* Korcsak-Gorzo, Stapmanns, and Espinoza Valverde et al. (in preparation).
131+
* Korcsak-Gorzo et al. (2025).
131132
*/
132133
template < typename targetidentifierT >
133134
class eprop_learning_signal_connection : public Connection< targetidentifierT >

‎models/eprop_learning_signal_connection_bsshslm_2020.h‎

Lines changed: 4 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -110,9 +110,10 @@ References
110110
networks of spiking neurons. Nature Communications, 11:3625.
111111
https://doi.org/10.1038/s41467-020-17236-y
112112
113-
.. [2] Korcsak-Gorzo A, Stapmanns J, Espinoza Valverde JA, Plesser HE,
114-
Dahmen D, Bolten M, Van Albada SJ, Diesmann M. Event-based
115-
implementation of eligibility propagation (in preparation)
113+
.. [2] Korcsak-Gorzo A, Espinoza Valverde JA, Stapmanns J, Plesser HE, Dahmen D,
114+
Bolten M, van Albada SJ, Diesmann M (2025). Event-driven eligibility
115+
propagation in large sparse networks: efficiency shaped by biological
116+
realism. arXiv:2511.21674. https://doi.org/10.48550/arXiv.2511.21674
116117
117118
See also
118119
++++++++

‎models/eprop_readout.h‎

Lines changed: 5 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -222,9 +222,10 @@ References
222222
networks of spiking neurons. Nature Communications, 11:3625.
223223
https://doi.org/10.1038/s41467-020-17236-y
224224
225-
.. [2] Korcsak-Gorzo A, Stapmanns J, Espinoza Valverde JA, Plesser HE,
226-
Dahmen D, Bolten M, Van Albada SJ, Diesmann M. Event-based
227-
implementation of eligibility propagation (in preparation)
225+
.. [2] Korcsak-Gorzo A, Espinoza Valverde JA, Stapmanns J, Plesser HE, Dahmen D,
226+
Bolten M, van Albada SJ, Diesmann M (2025). Event-driven eligibility
227+
propagation in large sparse networks: efficiency shaped by biological
228+
realism. arXiv:2511.21674. https://doi.org/10.48550/arXiv.2511.21674
228229
229230
Sends
230231
+++++
@@ -253,7 +254,7 @@ void register_eprop_readout( const std::string& name );
253254
*
254255
* Class implementing a current-based leaky integrate readout neuron model with delta-shaped postsynaptic currents for
255256
* e-prop plasticity according to Bellec et al. (2020) with additional biological features described in
256-
* Korcsak-Gorzo, Stapmanns, and Espinoza Valverde et al. (in preparation).
257+
* Korcsak-Gorzo et al. (2025).
257258
*/
258259
class eprop_readout : public EpropArchivingNodeReadout< false >
259260
{

‎models/eprop_readout_bsshslm_2020.h‎

Lines changed: 4 additions & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -217,9 +217,10 @@ References
217217
networks of spiking neurons. Nature Communications, 11:3625.
218218
https://doi.org/10.1038/s41467-020-17236-y
219219
220-
.. [2] Korcsak-Gorzo A, Stapmanns J, Espinoza Valverde JA, Plesser HE,
221-
Dahmen D, Bolten M, Van Albada SJ, Diesmann M. Event-based
222-
implementation of eligibility propagation (in preparation)
220+
.. [2] Korcsak-Gorzo A, Espinoza Valverde JA, Stapmanns J, Plesser HE, Dahmen D,
221+
Bolten M, van Albada SJ, Diesmann M (2025). Event-driven eligibility
222+
propagation in large sparse networks: efficiency shaped by biological
223+
realism. arXiv:2511.21674. https://doi.org/10.48550/arXiv.2511.21674
223224
224225
Sends
225226
+++++

0 commit comments

Comments
 (0)