E(2)-Equivariant Graph Planning for Navigation

We study E(2) Euclidean equivariance in navigation on geometric graphs and develop message passing network to solve it.

Equivariant Single View Pose Prediction Via Induced and Restriction Representations

We train an equivariant network for pose prediction from single 2D image by using induced and restricted representations.

Integrating Symmetry into Differentiable Planning with Steerable Convolutions

We formulate how differentiable planning algorithms can exploit inherent symmetry in path planning problems, named SymPlan, and propose practical algorithms.

Scaling up and Stabilizing Differentiable Planning with Implicit Differentiation

We study how implicit differentiation helps scale up and improve convergence of differentiable planning algorithms.

Toward Compositional Generalization in Object‑Oriented World Modeling

We formulate compositional generalization in object-oriented world modeling, and propose a soft and efficient mechanism for practice.

Learning Symmetric Embeddings for Equivariant World Models

We learn latent representations enforced with known transformation laws (group action), and apply this idea on equivariant latent world modeling.

Deep Imitation Learning for Bimanual Robotic Manipulation

We present a deep imitation learning framework for robotic bimanual manipulation in a continuous state-action space.

Match Plan Generation in Web Search with Parameterized Action Reinforcement Learning

We propose a parameterized action reinforcement learning algorithm to improve the performance of match plan generation in Bing search.