Laplacian Representations for Decision-Time Planning

arXiv:2602.05031 · cs.LG · Submitted 2026-02-04 · Read on arXiv

cs.LG

Submitted: 2026-02-04

Updated: 2026-06-02

Code: https://github.com/machado-research/ALPS

Project page: https://dikshuy.github.io/ALPS/5

Terminology

• Benchmark — 1× in this paper · explained in 2 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Reinforcement Learning (RL) — 1× in this paper · explained in 25 episodes

Sources

• Layer Normalization
• D4RL: Datasets for Deep Data-Driven Reinforcement Learning
• Discovering Temporal Structure: An Overview of Hierarchical Reinforcement Learning
• Investigating Compounding Prediction Errors in Learned Dynamics Models
• Benchmarking Model-Based Reinforcement Learning

Related papers

• Polynomial-Augmented Neural Networks (PANNs) with Weak Orthogonality Constraints for Enhanced Function and PDE Approximation
• AIRL-S: Unifying Reinforcement Learning and Search-Based Test-Time Scaling via Adversarial Inverse Reinforcement Learning
• Transformers as Bayesian In-Context Experimenters: Smoothness-Adaptive Efficient ATE Estimation
• Convergence issues in Relational Concept Analysis based on AOC-posets
• Beliefs Beyond Posteriors: The Predictive Cost of ELBO Binding
• Understanding Diffusion Models via Ratio-Based Function Approximation with SignReLU Networks