1 citations · 1 across the 3 of their papers we have counts for
3 papers
stat.ML2025
Learning Spectral Methods by Transformers
Yihan He, Yuan Cao, Hong-Yu Chen +3
Transformers demonstrate significant advantages as the building block of modern LLMs. In this work, we study the capacities of Transformers in performing unsupervised learning. We…
stat.ML2024
Provably Optimal Memory Capacity for Modern Hopfield Models: Transformer-Compatible Dense Associative Memories as Spherical Codes
Jerry Yao-Chieh Hu, Dennis Wu, Han Liu
We study the optimal memorization capacity of modern Hopfield models and Kernelized Hopfield Models (KHMs), a transformer-compatible class of Dense Associative Memories. We present…
cs.LG2023★ 1 cited
STanHop: Sparse Tandem Hopfield Model for Memory-Enhanced Time Series Prediction
Dennis Wu, Jerry Yao-Chieh Hu, Weijian Li +2
We present STanHop-Net (Sparse Tandem Hopfield Network) for multivariate time series prediction with memory-enhanced capabilities. At the heart of our approach is STanHop, a novel…