9 citations · 17 across the 3 of their papers we have counts for
3 papers
cs.LG2023★ 9 cited
A new perspective on building efficient and expressive 3D equivariant graph neural networks
Weitao Du, Yuanqi Du, Limei Wang +5
Geometric deep learning enables the encoding of physical symmetries in modeling 3D objects. Despite rapid progress in encoding 3D symmetries into Graph Neural Networks (GNNs), a co…
cs.AI2022
Left Heavy Tails and the Effectiveness of the Policy and Value Networks in DNN-based best-first search for Sokoban Planning
Dieqiao Feng, Carla Gomes, Bart Selman
Despite the success of practical solvers in various NP-complete domains such as SAT and CSP as well as using deep reinforcement learning to tackle two-player games such as Go, cert…
cs.CV2016★ 8 cited
Training Bit Fully Convolutional Network for Fast Semantic Segmentation
He Wen, Shuchang Zhou, Zhe Liang +4
Fully convolutional neural networks give accurate, per-pixel prediction for input images and have applications like semantic segmentation. However, a typical FCN usually requires l…