Q.ANT Runs Generative AI on Photonic Hardware

Generative AI and Recurrent Networks run on Q.ANT's Second-Generation Photonic Processor Complexity Model Graph Climbing the ...
Nature

Learning long sequences in spiking neural networks

Spiking neural networks (SNNs) take inspiration from the brain to enable energy-efficient computations. Since the advent of Transformers, SNNs have struggled to compete with artificial networks on ...
Nature

Back to recurrent processing at the crossroad of transformers and state-space models

The outstanding results achieved by large language models (LLMs) 1,2 and by their even more recent multi-modal variants 3, rely on attention-based neural architectures with several analogies to the ...
Medical Xpress

A recurrent neural network-based framework to non-linearly model behaviorally relevant neural dynamics

A key objective of several neuroscience studies is to understand and model how the dynamics of distinct populations of neurons give rise to specific human and animal behaviors. Many existing methods ...
Booth School of Business

Paper Recurrent Neural Networks for Nonlinear Time Series

This study bridges classical time-series econometrics with modern machine learning by establishing theoretical performance guarantees for recurrent neural networks (RNNs) applied to complex ...