244 citations · 446 across the 7 of their papers we have counts for
9 papers
Neural Sampling Machine with Stochastic Synapse allows Brain-like Learning and Inference
Sourav Dutta, Georgios Detorakis, Abhishek Khanna +3
Many real-world mission-critical applications require continual online learning from noisy data and real-time decision making with a defined confidence level. Probabilistic models…
Randomized Self Organizing Map
Nicolas P. Rougier, Georgios Is. Detorakis
We propose a variation of the self organizing map algorithm by considering the random placement of neurons on a two-dimensional manifold, following a blue noise distribution from w…
Inherent Weight Normalization in Stochastic Neural Networks
Georgios Detorakis, Sourav Dutta, Abhishek Khanna +3
Multiplicative stochasticity such as Dropout improves the robustness and generalizability of deep neural networks. Here, we further demonstrate that always-on multiplicative stocha…
Contrastive Hebbian Learning with Random Feedback Weights
Georgios Detorakis, Travis Bartley, Emre Neftci
Neural networks are commonly trained to make predictions through learning algorithms. Contrastive Hebbian learning, which is a powerful rule inspired by gradient backpropagation, i…
Neural and Synaptic Array Transceiver: A Brain-Inspired Computing Framework for Embedded Learning
Georgios Detorakis, Sadique Sheik, Charles Augustine +6
Embedded, continual learning for autonomous and adaptive behavior is a key application of neuromorphic hardware. However, neuromorphic implementations of embedded learning at large…
Sustainable computational science: the ReScience initiative
Nicolas P. Rougier, Konrad Hinsen, Frédéric Alexandre +42
Computer science offers a large set of tools for prototyping, writing, running, testing, validating, sharing and reproducing results, however computational science lags behind. In…
Neuromorphic Deep Learning Machines
Emre Neftci, Charles Augustine, Somnath Paul +1
An ongoing challenge in neuromorphic computing is to devise general and computationally efficient models of inference and learning which are compatible with the spatial and tempora…
Forward Table-Based Presynaptic Event-Triggered Spike-Timing-Dependent Plasticity
Bruno U. Pedroni, Sadique Sheik, Siddharth Joshi +5
Spike-timing-dependent plasticity (STDP) incurs both causal and acausal synaptic weight updates, for negative and positive time differences between pre-synaptic and post-synaptic s…
SPySort: Neuronal Spike Sorting with Python
Christophe Pouzat, Georgios Is. Detorakis
Extracellular recordings with multi-electrode arrays is one of the basic tools of contemporary neuroscience. These recordings are mostly used to monitor the activities, understood…