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07/08/2021
A Long Short-Term Memory for AI Applications in Spike-based Neuromorphic Hardware
In spite of intensive efforts it has remained an open problem to what ex...
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06/27/2021
Pairing Conceptual Modeling with Machine Learning
Both conceptual modeling and machine learning have long been recognized ...
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05/12/2021
CCN GAC Workshop: Issues with learning in biological recurrent neural networks
This perspective piece came about through the Generative Adversarial Col...
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07/24/2020
Online Spatio-Temporal Learning in Deep Neural Networks
Biological neural networks are equipped with an inherent capability to c...
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03/03/2020
Embodied Synaptic Plasticity with Online Reinforcement learning
The endeavor to understand the brain involves multiple collaborating res...
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01/31/2020
Classifying Images with Few Spikes per Neuron
Spiking neural networks (SNNs) promise to provide AI implementations wit...
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12/30/2019
Recognizing Images with at most one Spike per Neuron
In order to port the performance of trained artificial neural networks (...
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09/16/2019
Reservoirs learn to learn
We consider reservoirs in the form of liquid state machines, i.e., recur...
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03/20/2019
Efficient Reward-Based Structural Plasticity on a SpiNNaker 2 Prototype
Advances in neuroscience uncover the mechanisms employed by the brain to...
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03/15/2019
Neuromorphic Hardware learns to learn
Hyperparameters and learning algorithms for neuromorphic hardware are us...
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01/25/2019
Biologically inspired alternatives to backpropagation through time for learning in recurrent neural nets
The way how recurrently connected networks of spiking neurons in the bra...
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10/28/2018
Smoothed Analysis of Discrete Tensor Decomposition and Assemblies of Neurons
We analyze linear independence of rank one tensors produced by tensor po...
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03/26/2018
Long short-term memory and Learning-to-learn in networks of spiking neurons
Networks of spiking neurons (SNNs) are frequently studied as models for ...
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11/14/2017
Deep Rewiring: Training very sparse deep networks
Neuromorphic hardware tends to pose limits on the connectivity of deep n...
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04/13/2017
Reward-based stochastic self-configuration of neural circuits
Synaptic connections between neurons in the brain are dynamic because of...
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03/17/2017
Pattern representation and recognition with accelerated analog neuromorphic systems
Despite being originally inspired by the central nervous system, artific...
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03/06/2017
Neuromorphic Hardware In The Loop: Training a Deep Spiking Network on the BrainScaleS Wafer-Scale System
Emulating spiking neural networks on analog neuromorphic hardware offers...
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06/01/2016
CaMKII activation supports reward-based neural network optimization through Hamiltonian sampling
Synaptic plasticity is implemented and controlled through over thousand ...
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04/20/2015
Network Plasticity as Bayesian Inference
General results from statistical learning theory suggest to understand n...
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12/18/2014