21 citations · 67 across the 17 of their papers we have counts for
4 papers · 1 filter
AIGS: Generating Science from AI-Powered Automated Falsification
Zijun Liu, Kaiming Liu, Yiqi Zhu +5
Rapid development of artificial intelligence has drastically accelerated the development of scientific discovery. Trained with large-scale observation data, deep neural networks ex…
Improving Adversarial Robustness of DEQs with Explicit Regulations Along the Neural Dynamics
Zonghan Yang, Peng Li, Tianyu Pang +1
Deep equilibrium (DEQ) models replace the multiple-layer stacking of conventional deep networks with a fixed-point iteration of a single-layer transformation. Having been demonstra…
A Closer Look at the Adversarial Robustness of Deep Equilibrium Models
Zonghan Yang, Tianyu Pang, Yang Liu
Deep equilibrium models (DEQs) refrain from the traditional layer-stacking paradigm and turn to find the fixed point of a single layer. DEQs have achieved promising performance on…
Restricted Orthogonal Gradient Projection for Continual Learning
Zeyuan Yang, Zonghan Yang, Peng Li +1
Continual learning aims to avoid catastrophic forgetting and effectively leverage learned experiences to master new knowledge. Existing gradient projection approaches impose hard c…