PhD in machine learning at Cambridge University. Previously at TU Munich.
STGCN-PyTorch. ๐ Implementation of spatio-temporal graph convolutional network with PyTorch
371Single-Player-MCTS. ๐ณ Python implementation of single-player Monte-Carlo Tree Search.
67Deep-Gaussian-Process. ๐คฟ Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0
25pnerf-pytorch. ๐ PyTorch implementation of the Parallelized Natural Extension Reference Frame algorithm
21Mobility-Flows-Neural-Networks. ๐ Learning Mobility Flows from Urban Features with Spatial Interaction Models and Neural Networks
20GGP-TF2. ๐ Implementation of the Graph Gaussian Process using GPflow and TensorFlow 2
10Swift-Machine-Learning-Library. ๐ฃ A machine learning library in Swift.
4Graph-Classification-Gaussian-Processes-via-Spectral-Features. Code for the UAI 2023 paper Graph Classification Gaussian Processes via Spectral Features
3Denoising-Diffusion-Probabilistic-Models-Playground. โจ๏ธ From scratch implementations of Denoising Diffusion Probabilistic Models for small toy examples to be run on local machines within minutes.
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