On Double Descent in Reinforcement Learning with LSTD and Random Features
No confident code implementation found for this paper. 1 possible match can be shown below.
No confident code implementation found for this paper. 1 possible match can be shown below.
No confident code match yet
We couldn't find an author-owned or strongly-evidenced community implementation for this paper. 1 weaker match is hidden by default — verify before relying on them.
No code implementations found yet.
Know of an implementation? Let us know in the comments below!
Towards Robust 3D Object Detection with LiDAR and 4D Radar Fusion in Various Weather Conditions
Aligning with Logic: Measuring, Evaluating and Improving Logical Preference Consistency in Large Language Models
Discovering Features with Synergistic Interactions in Multiple Views
NeuralPlane: Structured 3D Reconstruction in Planar Primitives with Neural Fields
Augmenting Decision with Hypothesis in Reinforcement Learning
AlphaQCM: Alpha Discovery in Finance with Distributional Reinforcement Learning
@article{brellmann2026double,
title = {On Double Descent in Reinforcement Learning with LSTD and Random Features},
author = {David Brellmann and Eloise Berthier and David Filliat and Goran Frehse},
year = {2026},
url = {https://api.semanticscholar.org/CorpusID:44ad95c2c24cea2817d216b735f30e0432cd755d},
journal = {ICLR 2024 2024}
}Shows whether official code is linked for this paper.
[](https://codeofpaper.com/paper/44ad95c2c24cea2817d216b735f30e0432cd755d)