4 citations · 6 across the 7 of their papers we have counts for
3 papers · 1 filter
Layerwise Decoupling for Stable Structured Sparsification of Fully Connected Layers
Charles Kulick, Armenak Petrosyan, Sui Tang
We propose a decoupled, layerwise method for structurally sparsifying the fully connected layers of pretrained neural networks. Rather than penalizing all layers jointly, our appro…
Transformers Can Implement Preconditioned Richardson Iteration for In-Context Gaussian Kernel Regression
Mingsong Yan, Dongyang Li, Charles Kulick +1
In this paper, we study in-context kernel ridge regression (KRR) with Gaussian kernels and show, both theoretically and empirically, that a standard softmax-attention transformer c…
On the Convergence and Size Transferability of Continuous-depth Graph Neural Networks
Mingsong Yan, Charles Kulick, Sui Tang
Continuous-depth graph neural networks, also known as Graph Neural Differential Equations (GNDEs), combine the structural inductive bias of Graph Neural Networks (GNNs) with the co…