Search Results for author:
Found 9 papers, 6 papers with code
Cycle Invariant Positional Encoding for Graph Representation Learning
To efficiently encode the space of all cycles, we start with a cycle basis (i. e., a minimal set of cycles generating the cycle space) which we compute via the kernel of the 1-dimensional Hodge Laplacian of the input graph.
Efficiently Counting Substructures by Subgraph GNNs without Running GNN on Subgraphs
Among these works, a popular way is to use subgraph GNNs, which decompose the input graph into a collection of subgraphs and enhance the representation of the graph by applying GNN to individual subgraphs.
Neural Approximation of Graph Topological Features
Topological features based on persistent homology capture high-order structural information so as to augment graph neural network methods.
Cycle Representation Learning for Inductive Relation Prediction
In this paper, we consider rules as cycles and show that the space of cycles has a unique structure based on the mathematics of algebraic topology.
Graph Representation Learning
Inductive Relation Prediction
+1
A Topological View of Rule Learning in Knowledge Graphs
We propose to collect cycle bases that span the space of cycles.
Handwritten Mathematical Expression Recognition with Bidirectionally Trained Transformer
Encoder-decoder models have made great progress on handwritten mathematical expression recognition recently.
Automatic Description Construction for Math Expression via Topic Relation Graph
In the Selector, a Topic Relation Graph (TRG) is proposed to obtain the relevant documents which contain the comprehensive information of math expressions.
Link Prediction with Persistent Homology: An Interactive View
Link prediction is an important learning task for graph-structured data.
ConvMath: A Convolutional Sequence Network for Mathematical Expression Recognition
Despite the recent advances in optical character recognition (OCR), mathematical expressions still face a great challenge to recognize due to their two-dimensional graphical layout.
Optical Character Recognition
Optical Character Recognition (OCR)
