51 citations · 60 across the 5 of their papers we have counts for
4 papers · 1 filter
Order parameters and phase transitions of continual learning in deep neural networks
Haozhe Shan, Qianyi Li, Haim Sompolinsky
Continual learning (CL) enables animals to learn new tasks without erasing prior knowledge. CL in artificial neural networks (NNs) is challenging due to catastrophic forgetting, wh…
Connecting NTK and NNGP: A Unified Theoretical Framework for Wide Neural Network Learning Dynamics
Yehonatan Avidan, Qianyi Li, Haim Sompolinsky
Artificial neural networks have revolutionized machine learning in recent years, but a complete theoretical framework for their learning process is still lacking. Substantial advan…
Globally Gated Deep Linear Networks
Qianyi Li, Haim Sompolinsky
Recently proposed Gated Linear Networks present a tractable nonlinear network architecture, and exhibit interesting capabilities such as learning with local error signals and reduc…
Statistical Mechanics of Deep Linear Neural Networks: The Back-Propagating Kernel Renormalization
Qianyi Li, Haim Sompolinsky
The success of deep learning in many real-world tasks has triggered an intense effort to understand the power and limitations of deep learning in the training and generalization of…