activity
20192023
most citedMemory Replay with Data Compression for Continual Learning

39 citations · 52 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CV2023

Optimisation-Based Multi-Modal Semantic Image Editing

Bowen Li, Yongxin Yang, Steven McDonagh +3

Image editing affords increased control over the aesthetics and content of generated images. Pre-existing works focus predominantly on text-based instructions to achieve desired im…

eess.IV2022

Split Hierarchical Variational Compression

Tom Ryder, Chen Zhang, Ning Kang +1

Variational autoencoders (VAEs) have witnessed great success in performing the compression of image datasets. This success, made possible by the bits-back coding framework, has pro…

cs.LG202239 cited

Memory Replay with Data Compression for Continual Learning

Liyuan Wang, Xingxing Zhang, Kuo Yang +7

Continual learning needs to overcome catastrophic forgetting of the past. Memory replay of representative old training samples has been shown as an effective solution, and achieves…

cs.LG20211 cited

OSOA: One-Shot Online Adaptation of Deep Generative Models for Lossless Compression

Chen Zhang, Shifeng Zhang, Fabio Maria Carlucci +1

Explicit deep generative models (DGMs), e.g., VAEs and Normalizing Flows, have shown to offer an effective data modelling alternative for lossless compression. However, DGMs themse…

cs.LG202112 cited

iFlow: Numerically Invertible Flows for Efficient Lossless Compression via a Uniform Coder

Shifeng Zhang, Ning Kang, Tom Ryder +1

It was estimated that the world produced () of data in 2020, resulting in the enormous costs of both data storage and transmission. Fortunately, rece…

cs.LG2021

iVPF: Numerical Invertible Volume Preserving Flow for Efficient Lossless Compression

Shifeng Zhang, Chen Zhang, Ning Kang +1

It is nontrivial to store rapidly growing big data nowadays, which demands high-performance lossless compression techniques. Likelihood-based generative models have witnessed their…