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Found 5 papers, 4 papers with code
Nonparametric Modern Hopfield Models
We present a nonparametric construction for deep learning compatible modern Hopfield models and utilize this framework to debut an efficient variant.
Uniform Memory Retrieval with Larger Capacity for Modern Hopfield Models
Specifically, we accomplish this by constructing a separation loss $\mathcal{L}_\Phi$ that separates the local minima of kernelized energy by separating stored memory patterns in kernel space.
STanHop: Sparse Tandem Hopfield Model for Memory-Enhanced Time Series Prediction
We present STanHop-Net (Sparse Tandem Hopfield Network) for multivariate time series prediction with memory-enhanced capabilities.
On Sparse Modern Hopfield Model
Building upon this, we derive the sparse memory retrieval dynamics from the sparse energy function and show its one-step approximation is equivalent to the sparse-structured attention.
HonestBait: Forward References for Attractive but Faithful Headline Generation
Current methods for generating attractive headlines often learn directly from data, which bases attractiveness on the number of user clicks and views.
