CrossQ with weight normalization scales to high update-to-data ratios and matches or outperforms reset-based baselines on 25 continuous control benchmarks.
CrossQ: Batch normalization in deep reinforcement learning for greater sample efficiency and simplicity
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
extension 1
citation-polarity summary
fields
cs.LG 1years
2025 1verdicts
CONDITIONAL 1roles
extension 1polarities
extend 1representative citing papers
citing papers explorer
-
Scaling Off-Policy Reinforcement Learning with Batch and Weight Normalization
CrossQ with weight normalization scales to high update-to-data ratios and matches or outperforms reset-based baselines on 25 continuous control benchmarks.