publications

2022

  1. AAAI
    Leaping Through Time with Gradient-based Adaptation for Recommendation
    Chairatanakul, Nuttapong, NT, Hoang, Liu, Xin, and Murata, Tsuyoshi
    In 36th AAAI Conference on Artificial Intelligence (AAAI) 2022
    HTML PDF
  2. ML
    Heterogeneous graph embedding with single-level aggregation and infomax encoding
    Chairatanakul, Nuttapong, Liu, Xin, NT, Hoang, and Murata, Tsuyoshi
    Machine Learning 2022
    HTML PDF

2021

  1. NeurIPS
    Learning on Random Balls is Sufficient for Estimating (Some) Graph Parameters
    Maehara, Takanori, and NT, Hoang
    In 35th Conference on Neural Information Processing System (NeurIPS) 2021
    PDF
  2. ICPR
    Revisiting Graph Neural Networks: Graph Filtering Perspective
    NT, Hoang, Maehara, Takanori, and Murata, Tsuyoshi
    In 25th International Conference on Pattern Recognition (ICPR) 2021
    HTML

2020

  1. ICML
    Graph Homomorphism Convolution
    NT, Hoang, and Maehara, Takanori
    In 37th International Conference on Machine Learning (ICML) 2020
    HTML PDF
  2. arXiv
    Adaptive Stacked Graph Filter
    NT, Hoang, Maehara, Takanori, and Murata, Tsuyoshi
    2020
    PDF

2019

  1. ICLR-LLD
    Learning graph neural networks with noisy labels
    NT, Hoang, Choong, Jun Jin, and Murata, Tsuyoshi
    In International Conference on Learning Representations (ICLR) Limited Label Data Workshop 2019
    PDF
  2. arXiv
    A Simple Proof of the Universality of Invariant/Equivariant Graph Neural Networks
    Maehara, Takanori, and NT, Hoang
    2019
    PDF
  3. arXiv
    Revisiting Graph Neural Networks: All We Have is Low-Pass Filters
    NT, Hoang, and Maehara, Takanori
    2019
    PDF

2017

  1. IJCAI-GRL
    Motif-Aware Graph Embedding
    NT, Hoang, and Murata, Tsuyoshi
    In International Joint Conference on Artificial Intelligence (IJCAI) Graph Representation Learning Workshop 2017