Search Results for author: Riccardo Mereu

Found 4 papers, 4 papers with code

Function-space Parameterization of Neural Networks for Sequential Learning

1 code implementation16 Mar 2024 Aidan Scannell, Riccardo Mereu, Paul Chang, Ella Tamir, Joni Pajarinen, Arno Solin

Our parameterization offers: (i) a way to scale function-space methods to large data sets via sparsification, (ii) retention of prior knowledge when access to past data is limited, and (iii) a mechanism to incorporate new data without retraining.

Continual Learning Gaussian Processes +1

Sparse Function-space Representation of Neural Networks

2 code implementations5 Sep 2023 Aidan Scannell, Riccardo Mereu, Paul Chang, Ella Tamir, Joni Pajarinen, Arno Solin

Deep neural networks (NNs) are known to lack uncertainty estimates and struggle to incorporate new data.

Learning Sequential Descriptors for Sequence-based Visual Place Recognition

1 code implementation8 Jul 2022 Riccardo Mereu, Gabriele Trivigno, Gabriele Berton, Carlo Masone, Barbara Caputo

In robotics, Visual Place Recognition is a continuous process that receives as input a video stream to produce a hypothesis of the robot's current position within a map of known places.

Position Visual Place Recognition

Deep Visual Geo-localization Benchmark

1 code implementation CVPR 2022 Gabriele Berton, Riccardo Mereu, Gabriele Trivigno, Carlo Masone, Gabriela Csurka, Torsten Sattler, Barbara Caputo

In this paper, we propose a new open-source benchmarking framework for Visual Geo-localization (VG) that allows to build, train, and test a wide range of commonly used architectures, with the flexibility to change individual components of a geo-localization pipeline.

Benchmarking Data Augmentation

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