49 citations · 77 across the 7 of their papers we have counts for
7 papers
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…
Graph Value Iteration
Dieqiao Feng, Carla P. Gomes, Bart Selman
In recent years, deep Reinforcement Learning (RL) has been successful in various combinatorial search domains, such as two-player games and scientific discovery. However, directly…
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…
A Novel Automated Curriculum Strategy to Solve Hard Sokoban Planning Instances
Dieqiao Feng, Carla P. Gomes, Bart Selman
In recent years, we have witnessed tremendous progress in deep reinforcement learning (RL) for tasks such as Go, Chess, video games, and robot control. Nevertheless, other combinat…
Solving Hard AI Planning Instances Using Curriculum-Driven Deep Reinforcement Learning
Dieqiao Feng, Carla P. Gomes, Bart Selman
Despite significant progress in general AI planning, certain domains remain out of reach of current AI planning systems. Sokoban is a PSPACE-complete planning task and represents o…
GeneGAN: Learning Object Transfiguration and Attribute Subspace from Unpaired Data
Shuchang Zhou, Taihong Xiao, Yi Yang +3
Object Transfiguration replaces an object in an image with another object from a second image. For example it can perform tasks like "putting exactly those eyeglasses from image A…