On the linearity of large non-linear models: when and why the tangent kernel is constant. - Chaoyue Liu 001; Libin Zhu; Mikhail Belkin (NeurIPS, 2020)

Toward a theory of optimization for over-parameterized systems of non-linear equations: the lessons of deep learning. - Chaoyue Liu 001; Libin Zhu; Mikhail Belkin (CoRR, 2020)

Transition to Linearity of Wide Neural Networks is an Emerging Property of Assembling Weak Models. - Chaoyue Liu 001; Libin Zhu; Mikhail Belkin (ICLR, 2022)

Transition to Linearity of General Neural Networks with Directed Acyclic Graph Architecture. - Libin Zhu; Chaoyue Liu 001; Mikhail Belkin (NeurIPS, 2022)

Quadratic models for understanding neural network dynamics. - Libin Zhu; Chaoyue Liu 001; Adityanarayanan Radhakrishnan; Mikhail Belkin (CoRR, 2022)

A note on Linear Bottleneck networks and their Transition to Multilinearity. - Libin Zhu; Parthe Pandit; Mikhail Belkin (CoRR, 2022)

Restricted Strong Convexity of Deep Learning Models with Smooth Activations. - Arindam Banerjee 001; Pedro Cisneros-Velarde; Libin Zhu; Mikhail Belkin (ICLR, 2023)

Neural tangent kernel at initialization: linear width suffices. - Arindam Banerjee 001; Pedro Cisneros-Velarde; Libin Zhu; Mikhail Belkin (UAI, 2023)

Quadratic models for understanding catapult dynamics of neural networks. - Libin Zhu; Chaoyue Liu 001; Adityanarayanan Radhakrishnan; Mikhail Belkin (ICLR, 2024)

Catapults in SGD: spikes in the training loss and their impact on generalization through feature learning. - Libin Zhu; Chaoyue Liu 001; Adityanarayanan Radhakrishnan; Mikhail Belkin (ICML, 2024)

Emergence in non-neural models: grokking modular arithmetic via average gradient outer product. - Neil Mallinar; Daniel Beaglehole; Libin Zhu; Adityanarayanan Radhakrishnan; Parthe Pandit; Mikhail Belkin (CoRR, 2024)

Toward Understanding the Dynamics of Over-parameterized Neural Networks - Libin Zhu (2024)

A Hyperspectral Feature Selection Method for Soil Organic Matter Estimation Based on an Improved Weighted Marine Predators Algorithm. - Kun Tan; Libin Zhu; Xue Wang 008 (IEEE Trans. Geosci. Remote. Sens., 2025)

Iteratively reweighted kernel machines efficiently learn sparse functions. - Libin Zhu; Damek Davis; Dmitriy Drusvyatskiy; Maryam Fazel (CoRR, 2025)