3 citations · 3 across the 2 of their papers we have counts for
2 papers
stat.ML2023★ 3 cited
Manifold Learning with Sparse Regularised Optimal Transport
Stephen Zhang, Gilles Mordant, Tetsuya Matsumoto +1
Manifold learning is a central task in modern statistics and data science. Many datasets (cells, documents, images, molecules) can be represented as point clouds embedded in a high…
stat.ML2022
Beyond kNN: Adaptive, Sparse Neighborhood Graphs via Optimal Transport
Tetsuya Matsumoto, Stephen Zhang, Geoffrey Schiebinger
Nearest neighbour graphs are widely used to capture the geometry or topology of a dataset. One of the most common strategies to construct such a graph is based on selecting a fixed…