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Found 5 papers, 5 papers with code
CLOOB: Modern Hopfield Networks with InfoLOOB Outperform CLIP
We suggest to use modern Hopfield networks to tackle the problem of explaining away.
A Dataset Perspective on Offline Reinforcement Learning
The dataset characteristics are determined by the behavioral policy that samples this dataset.
History Compression via Language Models in Reinforcement Learning
We propose to utilize a frozen Pretrained Language Transformer (PLT) for history representation and compression to improve sample efficiency.
Hopular: Modern Hopfield Networks for Tabular Data
In experiments on small-sized tabular datasets with less than 1, 000 samples, Hopular surpasses Gradient Boosting, Random Forests, SVMs, and in particular several Deep Learning methods.
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Reactive Exploration to Cope with Non-Stationarity in Lifelong Reinforcement Learning
Therefore, exploration strategies and learning methods are required that are capable of tracking the steady domain shifts, and adapting to them.
