3 citations · 6 across the 4 of their papers we have counts for
5 papers
RNN with Particle Flow for Probabilistic Spatio-temporal Forecasting
Soumyasundar Pal, Liheng Ma, Yingxue Zhang +1
Spatio-temporal forecasting has numerous applications in analyzing wireless, traffic, and financial networks. Many classical statistical models often fall short in handling the com…
Graph Attention Networks with Positional Embeddings
Liheng Ma, Reihaneh Rabbany, Adriana Romero-Soriano
Graph Neural Networks (GNNs) are deep learning methods which provide the current state of the art performance in node classification tasks. GNNs often assume homophily -- neighbori…
Knowledge-Enhanced Top-K Recommendation in Poincaré Ball
Chen Ma, Liheng Ma, Yingxue Zhang +3
Personalized recommender systems are increasingly important as more content and services become available and users struggle to identify what might interest them. Thanks to the abi…
Probabilistic Metric Learning with Adaptive Margin for Top-K Recommendation
Chen Ma, Liheng Ma, Yingxue Zhang +3
Personalized recommender systems are playing an increasingly important role as more content and services become available and users struggle to identify what might interest them. A…
Memory Augmented Graph Neural Networks for Sequential Recommendation
Chen Ma, Liheng Ma, Yingxue Zhang +3
The chronological order of user-item interactions can reveal time-evolving and sequential user behaviors in many recommender systems. The items that users will interact with may de…