What is PyKale?

PyKale is a Python library providing accessible machine learning from multiple data sources for interdisciplinary research, particularly multimodal learning and transfer learning, named collectively as Knowledge-aware machine learning (Kale).

✅ Listed in the official PyTorch Landscape as one of only four libraries under “Multimodal”, alongside MMF (Meta), NeMo (NVIDIA), and USB (Microsoft).

multiple-inputs-svgrepo-com
Multimodal/Transfer Learning

Learn from data of multiple sources (modalities / domains) under one roof.

universal-access-solid
Accessible Machine Learning

Separate code and configurations for non-programmers to configure systems without coding.

ai-platform-unified-svgrepo-com
Unified Pipeline-based API

All machine learning workflows follow a standardized six-step pipeline.

The Core PyKale Team

Avatar

Haiping Lu

Avatar

Lawrence Schobs

Avatar

Peizhen Bai

Avatar

Raivo Koot

Avatar

Robert Turner

Avatar

Shuo Zhou

Avatar

Xianyuan Liu

Developed mainly at the University of Sheffield, with partial support from an EPSRC NetworkPlus grant (UKRI396), a Wellcome Trust Innovator Award (215799/Z/19/Z), and university funding through the Centre for Machine Intelligence and its AI Research Engineering (AIRE) team.