Luca Pasa

Orcid: 0000-0002-3023-3046

According to our database1, Luca Pasa authored at least 29 papers between 2014 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Links

On csauthors.net:

Bibliography

2024
Empowering Simple Graph Convolutional Networks.
IEEE Trans. Neural Networks Learn. Syst., April, 2024

A unified framework for backpropagation-free soft and hard gated graph neural networks.
Knowl. Inf. Syst., April, 2024

Fair graph representation learning: Empowering NIFTY via Biased Edge Dropout and Fair Attribute Preprocessing.
Neurocomputing, January, 2024

"All of Me": Mining Users' Attributes from their Public Spotify Playlists.
CoRR, 2024

2023
Topology preserving maps as aggregations for Graph Convolutional Neural Networks.
Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing, 2023

2022
Multiresolution Reservoir Graph Neural Network.
IEEE Trans. Neural Networks Learn. Syst., 2022

SOM-based aggregation for graph convolutional neural networks.
Neural Comput. Appl., 2022

Polynomial-based graph convolutional neural networks for graph classification.
Mach. Learn., 2022

Compact graph neural network models for node classification.
Proceedings of the SAC '22: The 37th ACM/SIGAPP Symposium on Applied Computing, Virtual Event, April 25, 2022

Understanding Catastrophic Forgetting of Gated Linear Networks in Continual Learning.
Proceedings of the International Joint Conference on Neural Networks, 2022

Backpropagation-free Graph Neural Networks.
Proceedings of the IEEE International Conference on Data Mining, 2022

Biased Edge Dropout in NIFTY for Fair Graph Representation Learning.
Proceedings of the 30th European Symposium on Artificial Neural Networks, 2022

Deep Learning for Graphs.
Proceedings of the 30th European Symposium on Artificial Neural Networks, 2022

2021
Simple Graph Convolutional Networks.
CoRR, 2021

Simple Multi-resolution Gated GNN.
Proceedings of the IEEE Symposium Series on Computational Intelligence, 2021

Audio-Visual Target Speaker Enhancement on Multi-Talker Environment Using Event-Driven Cameras.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2021

Tangent Graph Convolutional Network.
Proceedings of the 29th European Symposium on Artificial Neural Networks, 2021

2020
An Analysis of Speech Enhancement and Recognition Losses in Limited Resources Multi-Talker Single Channel Audio-Visual ASR.
Proceedings of the 2020 IEEE International Conference on Acoustics, 2020

Deep Recurrent Graph Neural Networks.
Proceedings of the 28th European Symposium on Artificial Neural Networks, 2020

Linear Graph Convolutional Networks.
Proceedings of the 28th European Symposium on Artificial Neural Networks, 2020

2019
Audio-Visual Target Speaker Extraction on Multi-Talker Environment using Event-Driven Cameras.
CoRR, 2019

Joined Audio-Visual Speech Enhancement and Recognition in the Cocktail Party: The Tug Of War Between Enhancement and Recognition Losses.
CoRR, 2019

Threat is in the Air: Machine Learning for Wireless Network Applications.
Proceedings of the ACM Workshop on Wireless Security and Machine Learning, 2019

Face Landmark-based Speaker-independent Audio-visual Speech Enhancement in Multi-talker Environments.
Proceedings of the IEEE International Conference on Acoustics, 2019

2017
Linear dynamical based models for sequential domains.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

2016
Learning Sequential Data with the Help of Linear Systems.
Proceedings of the Artificial Neural Networks in Pattern Recognition, 2016

2015
Neural Networks for Sequential Data: a Pre-training Approach based on Hidden Markov Models.
Neurocomputing, 2015

2014
Pre-training of Recurrent Neural Networks via Linear Autoencoders.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

A HMM-based pre-training approach for sequential data.
Proceedings of the 22th European Symposium on Artificial Neural Networks, 2014


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