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Meeting ID: 933 1728 3997<br>
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Passcode: 059545
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### Reservoir computing and euler state networks (prelim. title)
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### Reservoir Computing and Beyond
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Claudio Gallicchio, Università di Pisa
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**Invitation**: Elisabeth Pfaehler
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#### Abstract
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Reservoir Computing is an appealing methodology to design deep neural networks for temporal data processing that is strikingly efficient in terms of required computational resources. The core working principle resides in imposing dynamical stability properties to the developed neural representations, and restricting the training algorithms to operate on a small set of connections. After an introduction to the topic, this seminar will delve into recent advances that enable state-of-the-art performance in problems on temporal and graph-structured data, at a fraction of the cost required by fully trainable models.
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#### Papers:
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* Gallicchio, Claudio. "Euler State Networks." arXiv preprint arXiv:2203.09382 (2022). [PDF](https://arxiv.org/pdf/2203.09382)
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* Gallicchio, Claudio, and Alessio Micheli. "Fast and deep graph neural networks." Proceedings of the AAAI conference on artificial intelligence. Vol. 34. No. 04. 2020. [PDF](https://ojs.aaai.org/index.php/AAAI/article/view/5803/5659)
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**Invitation and moderation**: Elisabeth Pfaehler
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## Past Meetings
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---
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last change: 21.11.2022 sw |
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\ No newline at end of file |
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last change: 23.11.2022 sw |
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