Zhaocheng Zhu
Zhaocheng Zhu
Mila - Quebec AI Institute
Verified email at - Homepage
Cited by
Cited by
KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language Representation
X Wang, T Gao, Z Zhu, Z Zhang, Z Liu, J Li, J Tang
Transactions of the Association for Computational Linguistics 9, 176-194, 2021
GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation
C Shi*, M Xu*, Z Zhu, W Zhang, M Zhang, J Tang
International Conference on Learning Representations, 2020
Neural bellman-ford networks: A general graph neural network framework for link prediction
Z Zhu, Z Zhang, LP Xhonneux, J Tang
Advances in Neural Information Processing Systems 34, 29476-29490, 2021
GraphVite: A High-Performance CPU-GPU Hybrid System for Node Embedding
Z Zhu, S Xu, M Qu, J Tang
The World Wide Web Conference, 2494-2504, 2019
TorchDrug: A Powerful and Flexible Machine Learning Platform for Drug Discovery
Z Zhu, C Shi, Z Zhang, S Liu, M Xu, X Yuan, Y Zhang, J Chen, H Cai, J Lu, ...
arXiv preprint arXiv:2202.08320, 2022
Neural-Symbolic Models for Logical Queries on Knowledge Graphs
Z Zhu, M Galkin, Z Zhang, J Tang
International Conference on Machine Learning, 2022
PEER: A Comprehensive and Multi-Task Benchmark for Protein Sequence Understanding
M Xu*, Z Zhang*, J Lu, Z Zhu, Y Zhang, C Ma, R Liu, J Tang
Advances in Neural Information Processing Systems, 2022
Dialog state tracking with attention-based sequence-to-sequence learning
T Hori, H Wang, C Hori, S Watanabe, B Harsham, J Le Roux, JR Hershey, ...
2016 IEEE Spoken Language Technology Workshop (SLT), 552-558, 2016
GraphText: Graph Reasoning in Text Space
J Zhao, L Zhuo, Y Shen, M Qu, K Liu, M Bronstein, Z Zhu, J Tang
arXiv preprint arXiv:2310.01089, 2023
Large Language Models can Learn Rules
Z Zhu, Y Xue, X Chen, D Zhou, J Tang, D Schuurmans, H Dai
arXiv preprint arXiv:2310.07064, 2023
Self-Adaptive Network Pruning
J Chen, Z Zhu, C Li, Y Zhao
International Conference on Neural Information Processing, 175-186, 2019
Neural Graph Reasoning: Complex Logical Query Answering Meets Graph Databases
H Ren, M Galkin, M Cochez, Z Zhu, J Leskovec
arXiv preprint arXiv:2303.14617, 2023
Towards Foundation Models for Knowledge Graph Reasoning
M Galkin, X Yuan, H Mostafa, J Tang, Z Zhu
arXiv preprint arXiv:2310.04562, 2023
Inductive logical query answering in knowledge graphs
M Galkin, Z Zhu, H Ren, J Tang
Advances in Neural Information Processing Systems 35, 15230-15243, 2022
A* net: A scalable path-based reasoning approach for knowledge graphs
Z Zhu*, X Yuan*, M Galkin, LP Xhonneux, M Zhang, M Gazeau, J Tang
Advances in Neural Information Processing Systems 36, 2023
Context Aware Document Embedding
Z Zhu, J Hu
arXiv preprint arXiv:1707.01521, 2017
Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets
D Beaini, S Huang, JA Cunha, G Moisescu-Pareja, O Dymov, ...
arXiv preprint arXiv:2310.04292, 2023
Zero-shot Logical Query Reasoning on any Knowledge Graph
M Galkin, J Zhou, B Ribeiro, J Tang, Z Zhu
arXiv preprint arXiv:2404.07198, 2024
GraphAny: A Foundation Model for Node Classification on Any Graph
J Zhao, H Mostafa, M Galkin, M Bronstein, Z Zhu, J Tang
arXiv preprint arXiv:2405.20445, 2024
Saliency Supervision: An intuitive and effective approach for pain intensity regression
C Li, Z Zhu, Y Zhao
Neural Information Processing: 25th International Conference, ICONIP 2018 …, 2018
The system can't perform the operation now. Try again later.
Articles 1–20