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Found 4 papers, 3 papers with code
Open RL Benchmark: Comprehensive Tracked Experiments for Reinforcement Learning
As a result, it is usually necessary to reproduce the experiments from scratch, which can be time-consuming and error-prone.
Teacher-Generated Spatial-Attention Labels Boost Robustness and Accuracy of Contrastive Models
We then traina model with a primary contrastive objective; to this stan-dard configuration, we add a simple output head trained topredict the attentional map for each image, guided by thepseudo labels from teacher model.
CleanRL: High-quality Single-file Implementations of Deep Reinforcement Learning Algorithms
CleanRL is an open-source library that provides high-quality single-file implementations of Deep Reinforcement Learning algorithms.
Rotation, Translation, and Cropping for Zero-Shot Generalization
Deep Reinforcement Learning (DRL) has shown impressive performance on domains with visual inputs, in particular various games.
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