Wednesday, 16 March 2022

A new paper on Online Spatio-Temporal Learning in Deep Neural Networks

Today our new paper about Online Spatio-Temporal Learning (OSTL) in Deep Neural Networks has been published in Transactions on Neural Networks and Learning Systems (IEEE). You are very welcome to read it here

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Tuesday, 1 March 2022

Our paper presented at the prestigious ISSCC!

Our new paper about the ReckOn chip, developed within the SMALL project, has just been presented at the 2022 International Solid-State Circuits Conference. You can read about our chip and its capabilities here.

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Monday, 10 January 2022

A book chapter on spike-based symbolic computations

Our SMALL consortium is wishing you all a prosperous new year!

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Sunday, 26 September 2021

Robot arm control with spiking RNNs - paper accepted to 2021 IEEE/RSJ IROS

September 2021 was a successful month for SMALL! A new paper, dealing with many-joint robot arm control with recurrent spiking neural networks (RNNs), has been accepted to the 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021 (preprint).

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Saturday, 25 September 2021

A preprint of our new paper on memristive neuromorphic RNNs is now available

We present a simulation framework of differential-architecture crossbar arrays based on an accurate and comprehensive Phase-Change Memory (PCM) device model, enabling online learning in memristive neuromorphic recurrent neural networks (RNNs). The preprint of our paper is now available here.

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Monday, 26 July 2021

Our new research on spike frequency adaptation published on eLife

Creating biologically realistic models for the underlying computations, especially with spiking neurons and for behaviorally relevant integration time spans, is notoriously difficult. We examine the role of spike frequency adaptation in such computations and find that it has a surprisingly large impact. Details on this research are now published on eLife.

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Tuesday, 16 February 2021

PCM-trace paper accepted to ISCAS 2021

PCM-trace is our new neuromorphic building block, which exploits the drift behavior of phase-change materials to implement long lasting eligibility traces, a critical ingredient of spike-based learning rules. The paper describing this novel solution has been accepted to the IEEE International Symposium on Circuits and Systems (ISCAS) 2021 (PDF).

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Monday, 23 November 2020

Accelerating Spiking Neural Networks using Memristive Crossbar Arrays

Our results on the usage of phase-change memory devices in spiking neural networks were published in the 27th IEEE International Conference on Electronics, Circuits and Systems (PDF).

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Sunday, 15 November 2020

Paper accepted for NeurIPS 2020

A paper on the integration of brain-like memory in deep neural network models was accepted for publication in the Proceedings of Advances in Neural Information Processing Systems 2020 (PDF).

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Thursday, 1 October 2020

Bidirectional Volatile Signatures of Metal–Oxide Memristors

Results of our comprehensive study for characterizing the relaxation dynamics of TiOx resistive RAM (RRAM) devices within a predefined volatility framework have been published (Part I: Characterization). In part II of this study, we have also presented a modeling framework that can account for RRAM relaxation characteristics (Part II: Modeling).

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Wednesday, 25 March 2020

Website launched

The website for the SMALL project has been launched! Be sure to check regularly the news section to stay updated about the progress of the project.

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