activity
20202022
most citedFrom Canonical Correlation Analysis to Self-supervised Graph Neural Networks

49 citations · 96 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2022★ 3 cited

Conservative Distributional Reinforcement Learning with Safety Constraints

Hengrui Zhang, Youfang Lin, Sheng Han +2

Safety exploration can be regarded as a constrained Markov decision problem where the expected long-term cost is constrained. Previous off-policy algorithms convert the constrained…

cs.LG2021★ 21 cited

Understanding GNN Computational Graph: A Coordinated Computation, IO, and Memory Perspective

Hengrui Zhang, Zhongming Yu, Guohao Dai +4

Graph Neural Networks (GNNs) have been widely used in various domains, and GNNs with sophisticated computational graph lead to higher latency and larger memory consumption. Optimiz…

cs.LG2021★ 49 cited

From Canonical Correlation Analysis to Self-supervised Graph Neural Networks

Hengrui Zhang, Qitian Wu, Junchi Yan +2

We introduce a conceptually simple yet effective model for self-supervised representation learning with graph data. It follows the previous methods that generate two views of an in…

cs.RO2021★ 11 cited

Super Odometry: IMU-centric LiDAR-Visual-Inertial Estimator for Challenging Environments

Shibo Zhao, Hengrui Zhang, Peng Wang +2

We propose Super Odometry, a high-precision multi-modal sensor fusion framework, providing a simple but effective way to fuse multiple sensors such as LiDAR, camera, and IMU sensor…

cs.IR2020★ 12 cited

Towards Open-World Recommendation: An Inductive Model-based Collaborative Filtering Approach

Qitian Wu, Hengrui Zhang, Xiaofeng Gao +2

Recommendation models can effectively estimate underlying user interests and predict one's future behaviors by factorizing an observed user-item rating matrix into products of two…