141 citations · 573 across the 21 of their papers we have counts for
8 papers · 1 filter
EasyTPP: Towards Open Benchmarking Temporal Point Processes
Siqiao Xue, Xiaoming Shi, Zhixuan Chu +9
Continuous-time event sequences play a vital role in real-world domains such as healthcare, finance, online shopping, social networks, and so on. To model such data, temporal point…
Directional diffusion models for graph representation learning
Run Yang, Yuling Yang, Fan Zhou +1
In recent years, diffusion models have achieved remarkable success in various domains of artificial intelligence, such as image synthesis, super-resolution, and 3D molecule generat…
Predicting Human Mobility via Self-supervised Disentanglement Learning
Qiang Gao, Jinyu Hong, Xovee Xu +3
Deep neural networks have recently achieved considerable improvements in learning human behavioral patterns and individual preferences from massive spatial-temporal trajectories da…
Non-decreasing Quantile Function Network with Efficient Exploration for Distributional Reinforcement Learning
Fan Zhou, Zhoufan Zhu, Qi Kuang +1
Although distributional reinforcement learning (DRL) has been widely examined in the past few years, there are two open questions people are still trying to address. One is how to…
Relational State-Space Model for Stochastic Multi-Object Systems
Fan Yang, Ling Chen, Fan Zhou +2
Real-world dynamical systems often consist of multiple stochastic subsystems that interact with each other. Modeling and forecasting the behavior of such dynamics are generally not…
Meta-GNN: On Few-shot Node Classification in Graph Meta-learning
Fan Zhou, Chengtai Cao, Kunpeng Zhang +3
Meta-learning has received a tremendous recent attention as a possible approach for mimicking human intelligence, i.e., acquiring new knowledge and skills with little or even no de…
A Distributed Hierarchical SGD Algorithm with Sparse Global Reduction
Fan Zhou, Guojing Cong
Reducing communication in training large-scale machine learning applications on distributed platform is still a big challenge. To address this issue, we propose a distributed hiera…
On the convergence properties of a -step averaging stochastic gradient descent algorithm for nonconvex optimization
Fan Zhou, Guojing Cong
Despite their popularity, the practical performance of asynchronous stochastic gradient descent methods (ASGD) for solving large scale machine learning problems are not as good as…