21 citations · 61 across the 10 of their papers we have counts for
10 papers
Graph Positional and Structural Encoder
Semih Cantürk, Renming Liu, Olivier Lapointe-Gagné +4
Positional and structural encodings (PSE) enable better identifiability of nodes within a graph, rendering them essential tools for empowering modern GNNs, and in particular graph…
Single-Cell Multimodal Prediction via Transformers
Wenzhuo Tang, Hongzhi Wen, Renming Liu +5
The recent development of multimodal single-cell technology has made the possibility of acquiring multiple omics data from individual cells, thereby enabling a deeper understanding…
Single Cells Are Spatial Tokens: Transformers for Spatial Transcriptomic Data Imputation
Hongzhi Wen, Wenzhuo Tang, Wei Jin +7
Spatially resolved transcriptomics brings exciting breakthroughs to single-cell analysis by providing physical locations along with gene expression. However, as a cost of the extre…
Deep Learning in Single-Cell Analysis
Dylan Molho, Jiayuan Ding, Zhaoheng Li +12
Single-cell technologies are revolutionizing the entire field of biology. The large volumes of data generated by single-cell technologies are high-dimensional, sparse, heterogeneou…
Taxonomy of Benchmarks in Graph Representation Learning
Renming Liu, Semih Cantürk, Frederik Wenkel +9
Graph Neural Networks (GNNs) extend the success of neural networks to graph-structured data by accounting for their intrinsic geometry. While extensive research has been done on de…
Towards a Taxonomy of Graph Learning Datasets
Renming Liu, Semih Cantürk, Frederik Wenkel +10
Graph neural networks (GNNs) have attracted much attention due to their ability to leverage the intrinsic geometries of the underlying data. Although many different types of GNN mo…
Accurately Modeling Biased Random Walks on Weighted Graphs Using
Renming Liu, Matthew Hirn, Arjun Krishnan
Node embedding is a powerful approach for representing the structural role of each node in a graph. is a widely used method for node embedding that works by exp…
Market Design for Tradable Mobility Credits
Siyu Chen, Ravi Seshadri, Carlos Lima Azevedo +5
Tradable mobility credit (TMC) schemes are an approach to travel demand management that have received significant attention in recent years. This paper proposes and analyzes altern…
Bayesian Optimization of Area-based Road Pricing
Renming Liu, Yu Jiang, Carlos Lima Azevedo
This study presents a Bayesian Optimization framework for area- and distance-based time-of-day pricing (TODP) for urban networks. The road pricing optimization problem can reach hi…
Managing network congestion with a tradable credit scheme: a trip-based MFD approach
Renming Liu, Siyu Chen, Yu Jiang +3
This study investigates the efficiency and effectiveness of an area-based tradable credit scheme (TCS) using the trip-based Macroscopic Fundamental Diagram model for the morning co…