A framework for grassroots research collaboration in machine learning and global health
C. Currin, M.N. Asiedu , C. Fourie, B. Rosman, H. Turki, A. Lambebo Tonja, J. Abbott, M. Ajala, S.A. Adedayo, C.C. Emezue, D. Machangara, in:, 1st Workshop on Machine Learning &; Global Health, OpenReview, 2023.

Predictive learning enables neural networks to learn complex working memory tasks
T.L. Van Der Plas, T.P. Vogels, S.G. Manohar, in:, Proceedings of Machine Learning Research, ML Research Press, 2022, pp. 518–531.

Developmentally regulated impairment of parvalbumin interneuron synaptic transmission in an experimental model of Dravet syndrome
K. Kaneko, C. Currin, K.M. Goff, E.R. Wengert, A. Somarowthu, T.P. Vogels, E.M. Goldberg, Cell Reports 38 (2022).

Developmental depression-to-facilitation shift controls excitation-inhibition balance
D.W. Jia, T.P. Vogels, R.P. Costa, Communications Biology 5 (2022).

Regimes and mechanisms of transient amplification in abstract and biological neural networks
G. Christodoulou, T.P. Vogels, E.J. Agnes, PLoS Computational Biology 18 (2022).

Depolarization of echo chambers by random dynamical nudge
C. Currin, S.V. Vera, A. Khaledi-Nasab, Scientific Reports 12 (2022).

A familiar thought: Machines that replace us?
B.J. Confavreux, T.P. Vogels, Neuron 110 (2022) 361–362.

High capacity and dynamic accessibility in associative memory networks with context-dependent neuronal and synaptic gating
W.F. Podlaski, E.J. Agnes, T.P. Vogels, BioRxiv (2022).

Online learning of neural computations from sparse temporal feedback
L. Braun, T.P. Vogels, in:, Advances in Neural Information Processing Systems - 35th Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2021, pp. 16437–16450.

The remarkable robustness of surrogate gradient learning for instilling complex function in spiking neural networks
F. Zenke, T.P. Vogels, Neural Computation 33 (2021) 899–925.

Talking science, online
P. Bozelos, T.P. Vogels, Nature Reviews Neuroscience 22 (2021) 1–2.

Towards democratizing and automating online conferences: Lessons from the Neuromatch Conferences
T. Achakulvisut, T. Ruangrong, P. Mineault, T.P. Vogels, M.A.K. Peters, P. Poirazi, C. Rozell, B. Wyble, D.F.M. Goodman, K.P. Kording, Trends in Cognitive Sciences 25 (2021) 265–268.

Training deep neural density estimators to identify mechanistic models of neural dynamics
P.J. Gonçalves, J.-M. Lueckmann, M. Deistler, M. Nonnenmacher, K. Öcal, G. Bassetto, C. Chintaluri, W.F. Podlaski, S.A. Haddad, T.P. Vogels, D.S. Greenberg, J.H. Macke, ELife 9 (2020).

Complementary inhibitory weight profiles emerge from plasticity and allow attentional switching of receptive fields
E.J. Agnes, A.I. Luppi, T.P. Vogels, The Journal of Neuroscience 40 (2020) 9634–9649.

A meta-learning approach to (re)discover plasticity rules that carve a desired function into a neural network
B.J. Confavreux, F. Zenke, E.J. Agnes, T. Lillicrap, T.P. Vogels, in:, Advances in Neural Information Processing Systems, 2020, pp. 16398–16408.