GitHub

Accelerating Training with Neuron Interaction and Nowcasting Networks

We introduce the NiNo model predicting future (nowcasting) parameters by learning neuron interaction in vision and language tasks. We feed c (c=5 by default) past parameter states as input to NiNo and ...
IEEE

Efficient Deep Neural Network Training With a Novel 5.3-Bit Block Floating Point Data Format

Abstract: Low-bit-width data formats offer a promising solution for enhancing the energy efficiency of Deep Neural Network (DNN) training accelerators. In this work, we introduce a novel 5.3-bit data ...
GitHub

Coupling LSTM Neural Networks and State-Space Models through Analytically Tractable Inference

This repo contains the matlab codes to reproduce the results for the paper: Vuong, Nguyen & Goulet (2024), Coupling LSTM Neural Networks and State-Space Models through Analytically Tractable Inference ...
IEEE

Quantum-Assisted Hierarchical Fuzzy Neural Network for Image Classification

Abstract: Deep learning is a powerful technique for data-driven learning in the era of Big Data. However, most deep learning models are deterministic models that ignore the uncertainty of data. Fuzzy ...