activity
20142024
most citedKernel Methods on Riemannian Manifolds with Gaussian RBF Kernels

259 citations · 329 across the 22 of their papers we have counts for

collaborators

22 papers

cs.CV2024

Backpropagation-free Network for 3D Test-time Adaptation

Yanshuo Wang, Ali Cheraghian, Zeeshan Hayder +7

Real-world systems often encounter new data over time, which leads to experiencing target domain shifts. Existing Test-Time Adaptation (TTA) methods tend to apply computationally h…

cs.CV2024

Text-Enhanced Data-free Approach for Federated Class-Incremental Learning

Minh-Tuan Tran, Trung Le, Xuan-May Le +2

Federated Class-Incremental Learning (FCIL) is an underexplored yet pivotal issue, involving the dynamic addition of new classes in the context of federated learning. In this field…

eess.AS2023

Real-time Neonatal Chest Sound Separation using Deep Learning

Yang Yi Poh, Ethan Grooby, Kenneth Tan +6

Auscultation for neonates is a simple and non-invasive method of providing diagnosis for cardiovascular and respiratory disease. Such diagnosis often requires high-quality heart an…

cs.LG2023

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…

cs.CV2023

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…

cs.CV20234 cited

Hyperbolic Geometry in Computer Vision: A Survey

Pengfei Fang, Mehrtash Harandi, Trung Le +1

Hyperbolic geometry, a Riemannian manifold endowed with constant sectional negative curvature, has been considered an alternative embedding space in many learning scenarios, \eg, n…