108 citations · 417 across the 27 of their papers we have counts for
6 papers · 1 filter
GeoAdapt: Self-Supervised Test-Time Adaptation in LiDAR Place Recognition Using Geometric Priors
Joshua Knights, Stephen Hausler, Sridha Sridharan +2
LiDAR place recognition approaches based on deep learning suffer from significant performance degradation when there is a shift between the distribution of training and test datase…
L3DMC: Lifelong Learning using Distillation via Mixed-Curvature Space
Kaushik Roy, Peyman Moghadam, Mehrtash Harandi
The performance of a lifelong learning (L3) model degrades when it is trained on a series of tasks, as the geometrical formation of the embedding space changes while learning novel…
Subspace Distillation for Continual Learning
Kaushik Roy, Christian Simon, Peyman Moghadam +1
An ultimate objective in continual learning is to preserve knowledge learned in preceding tasks while learning new tasks. To mitigate forgetting prior knowledge, we propose a novel…
Deep Robust Multi-Robot Re-localisation in Natural Environments
Milad Ramezani, Ethan Griffiths, Maryam Haghighat +2
The success of re-localisation has crucial implications for the practical deployment of robots operating within a prior map or relative to one another in real-world scenarios. Usin…
Exploiting Field Dependencies for Learning on Categorical Data
Zhibin Li, Piotr Koniusz, Lu Zhang +2
Traditional approaches for learning on categorical data underexploit the dependencies between columns (\aka fields) in a dataset because they rely on the embedding of data points d…
Learning Partial Correlation based Deep Visual Representation for Image Classification
Saimunur Rahman, Piotr Koniusz, Lei Wang +3
Visual representation based on covariance matrix has demonstrates its efficacy for image classification by characterising the pairwise correlation of different channels in convolut…