research
∙
10/27/2022
Transformers meet Stochastic Block Models: Attention with Data-Adaptive Sparsity and Cost
To overcome the quadratic cost of self-attention, recent works have prop...
share
research
∙
07/21/2022
Grounding Visual Representations with Texts for Domain Generalization
Reducing the representational discrepancy between source and target doma...
research
∙
07/06/2022
Pure Transformers are Powerful Graph Learners
We show that standard Transformers without graph-specific modifications ...
research
∙
11/24/2021
Supervised Neural Discrete Universal Denoiser for Adaptive Denoising
We improve the recently developed Neural DUDE, a neural network-based ad...
research
∙
07/23/2021
TargetNet: Functional microRNA Target Prediction with Deep Neural Networks
MicroRNAs (miRNAs) play pivotal roles in gene expression regulation by b...
research
∙
10/31/2017