6 citations · 13 across the 6 of their papers we have counts for
7 papers
Stochastic Adaptive Fourier Decomposition for Operator Learning
Pengqing Shi, Liming Zhang, Tao Qian +3
Fourier Neural Operators (FNOs) offer an efficient paradigm for solving partial differential equations (PDEs). However, FNOs rely on a fixed Fourier basis and hard frequency trunca…
SirenFNO: Efficient and Full Frequency Learning of Fourier Neural Operators
Pengqing Shi, Jie Yin, Stephen Tierney +1
Fourier neural operators (FNOs) are effective and efficient surrogates for approximating solutions of PDEs and generalize across discretizations. However, owing to the reliance on…
Collaborative Low-Rank Subspace Clustering
Stephen Tierney, Yi Guo, Junbin Gao
In this paper we present Collaborative Low-Rank Subspace Clustering. Given multiple observations of a phenomenon we learn a unified representation matrix. This unified matrix incor…
Tractable Clustering of Data on the Curve Manifold
Stephen Tierney, Junbin Gao, Yi Guo +1
In machine learning it is common to interpret each data point as a vector in Euclidean space. However the data may actually be functional i.e.\ each data point is a function of som…
Efficient Sparse Subspace Clustering by Nearest Neighbour Filtering
Stephen Tierney, Yi Guo, Junbin Gao
Sparse Subspace Clustering (SSC) has been used extensively for subspace identification tasks due to its theoretical guarantees and relative ease of implementation. However SSC has…
Low-Rank Representation over the Manifold of Curves
Stephen Tierney, Junbin Gao, Yi Guo +1
In machine learning it is common to interpret each data point as a vector in Euclidean space. However the data may actually be functional i.e.\ each data point is a function of som…
Segmentation of Subspaces in Sequential Data
Stephen Tierney, Yi Guo, Junbin Gao
We propose Ordered Subspace Clustering (OSC) to segment data drawn from a sequentially ordered union of subspaces. Similar to Sparse Subspace Clustering (SSC) we formulate the prob…