Publications

(2022). Self-supervised Learning Through Efference Copies. NeurIPS 2022.

Cite arXiv NeurIPS 2022 OpenReview

(2022). 2022 roadmap on neuromorphic computing and engineering. IOP Publishing.

Cite DOI IOP Publishing

(2021). Reservoirs learn to learn. Reservoir Computing.

Cite DOI Reservoir Computing - Springer

(2021). Visualizing a joint future of neuroscience and neuromorphic engineering. Neuron.

Cite DOI Neuron

(2020). Slow processes of neurons enable a biologically plausible approximation to policy gradient. NeurIPS 2019 - Biological and Artificial RL.

Workshop Homepage Contributed Talk

(2020). One-shot learning with spiking neural networks. bioRxiv.

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(2020). A solution to the learning dilemma for recurrent networks of spiking neurons. Nature Communications.

Cite DOI Nature Communications Code

(2019). Eligibility traces provide a data-inspired alternative to backpropagation through time. NeurIPS 2019 - Real Neurons & Hidden Units workshop.

OpenReview Workshop Homepage Contributed Talk

(2019). Neuromorphic Hardware Learns to Learn. Neuromorphic Hardware Learns to Learn.

Cite DOI Frontiers in Neuroscience Code

(2019). Biologically inspired alternatives to backpropagation through time for learning in recurrent neural nets. arXiv.

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