Activation function dependence of the storage capacity of treelike neural networks. - Jacob A. Zavatone-Veth; Cengiz Pehlevan (CoRR, 2020)

Depth induces scale-averaging in overparameterized linear Bayesian neural networks. - Jacob A. Zavatone-Veth; Cengiz Pehlevan (ACSCC, 2021)

Asymptotics of representation learning in finite Bayesian neural networks. - Jacob A. Zavatone-Veth; Abdulkadir Canatar; Benjamin S. Ruben; Cengiz Pehlevan (NeurIPS, 2021)

Exact marginal prior distributions of finite Bayesian neural networks. - Jacob A. Zavatone-Veth; Cengiz Pehlevan (NeurIPS, 2021)

Exact priors of finite neural networks. - Jacob A. Zavatone-Veth; Cengiz Pehlevan (CoRR, 2021)

Asymptotics of representation learning in finite Bayesian neural networks. - Jacob A. Zavatone-Veth; Abdulkadir Canatar; Cengiz Pehlevan (CoRR, 2021)

Natural gradient enables fast sampling in spiking neural networks. - Paul Masset; Jacob A. Zavatone-Veth; J. Patrick Connor; Venkatesh Murthy; Cengiz Pehlevan (NeurIPS, 2022)

Drifting neuronal representations: Bug or feature? - Paul Masset; Shanshan Qin; Jacob A. Zavatone-Veth (Biol. Cybern., 2022)

Contrasting random and learned features in deep Bayesian linear regression. - Jacob A. Zavatone-Veth; William L. Tong; Cengiz Pehlevan (CoRR, 2022)

On Neural Network Kernels and the Storage Capacity Problem. - Jacob A. Zavatone-Veth; Cengiz Pehlevan (Neural Comput., 2022)

Long Sequence Hopfield Memory. - Hamza Tahir Chaudhry; Jacob A. Zavatone-Veth; Dmitry Krotov; Cengiz Pehlevan (NeurIPS, 2023)

Neural Circuits for Fast Poisson Compressed Sensing in the Olfactory Bulb. - Jacob A. Zavatone-Veth; Paul Masset; William L. Tong; Joseph D. Zak; Venkatesh Murthy; Cengiz Pehlevan (NeurIPS, 2023)

Learning Curves for Deep Structured Gaussian Feature Models. - Jacob A. Zavatone-Veth; Cengiz Pehlevan (NeurIPS, 2023)

Neural networks learn to magnify areas near decision boundaries. - Jacob A. Zavatone-Veth; Sheng Yang 004; Julian A. Rubinfien; Cengiz Pehlevan (CoRR, 2023)

Partial observation can induce mechanistic mismatches in data-constrained models of neural dynamics. - William Qian 001; Jacob A. Zavatone-Veth; Benjamin S. Ruben; Cengiz Pehlevan (NeurIPS, 2024)

Scaling and renormalization in high-dimensional regression. - Alexander B. Atanasov; Jacob A. Zavatone-Veth; Cengiz Pehlevan (CoRR, 2024)

Asymptotic theory of in-context learning by linear attention. - Yue M. Lu; Mary I. Letey; Jacob A. Zavatone-Veth; Anindita Maiti; Cengiz Pehlevan (CoRR, 2024)

Spectral regularization for adversarially-robust representation learning. - Sheng Yang 004; Jacob A. Zavatone-Veth; Cengiz Pehlevan (CoRR, 2024)

Risk and cross validation in ridge regression with correlated samples. - Alexander B. Atanasov; Jacob A. Zavatone-Veth; Cengiz Pehlevan (CoRR, 2024)

Two-Point Deterministic Equivalence for Stochastic Gradient Dynamics in Linear Models. - Alexander B. Atanasov; Blake Bordelon; Jacob A. Zavatone-Veth; Courtney Paquette; Cengiz Pehlevan (CoRR, 2025)