84 citations · 124 across the 11 of their papers we have counts for
11 papers
PlanDQ: Hierarchical Plan Orchestration via D-Conductor and Q-Performer
Chang Chen, Junyeob Baek, Fei Deng +3
Despite the recent advancements in offline RL, no unified algorithm could achieve superior performance across a broad range of tasks. Offline \textit{value function learning}, in p…
Slot State Space Models
Jindong Jiang, Fei Deng, Gautam Singh +2
Recent State Space Models (SSMs) such as S4, S5, and Mamba have shown remarkable computational benefits in long-range temporal dependency modeling. However, in many sequence modeli…
Simple Hierarchical Planning with Diffusion
Chang Chen, Fei Deng, Kenji Kawaguchi +2
Diffusion-based generative methods have proven effective in modeling trajectories with offline datasets. However, they often face computational challenges and can falter in general…
Facing Off World Model Backbones: RNNs, Transformers, and S4
Fei Deng, Junyeong Park, Sungjin Ahn
World models are a fundamental component in model-based reinforcement learning (MBRL). To perform temporally extended and consistent simulations of the future in partially observab…
Constructive Assimilation: Boosting Contrastive Learning Performance through View Generation Strategies
Ligong Han, Seungwook Han, Shivchander Sudalairaj +8
Transformations based on domain expertise (expert transformations), such as random-resized-crop and color-jitter, have proven critical to the success of contrastive learning techni…
Object-Centric Slot Diffusion
Jindong Jiang, Fei Deng, Gautam Singh +1
The recent success of transformer-based image generative models in object-centric learning highlights the importance of powerful image generators for handling complex scenes. Howev…