Software
- Xfer: Transfer and meta-learning in Python.
It includes code for quick and easy deep transfer learning, as well as implementation of various recently published methodologies related to deep transfer learning and meta-learning. The code is in Python, MXNet, and PyTorch.
Some of my older software:
- A unified toolbox which can be found
here and includes:
- Bayesian GP-LVM (with M. Titsias, N. Lawrence)
- Variational Gaussian Process Dynamical Systems (VGPDS) (with M. Titsias) and
- Manifold Relevance Determination (MRD) (with C. H. Ek)
- Deep Gaussian processes: code available in MATLAB and Python.
- I am also using GPy, a Gaussian Process framework written in Python and developed in Sheffield.
Tutorials
- Introductory tutorial on Gaussian processes with code [tutorial], [notebook]
- Introductory tutorial on deep learning (probabilistic perspective) [tutorial] [notebook]
- Transfer Learning Blog post.
Blog posts
- Graph foundation models for personalization [Blog post].
- Transfer Learning [Medium article].
- Meta-learning [Amazon.science].