Theory of Deep Learning III: explaining the non-overfitting puzzle. - Tomaso A. Poggio; Kenji Kawaguchi; Qianli Liao; Brando Miranda; Lorenzo Rosasco; Xavier Boix; Jack Hidary; Hrushikesh N. Mhaskar (CoRR, 2018)

Theory IIIb: Generalization in Deep Networks. - Tomaso A. Poggio; Qianli Liao; Brando Miranda; Andrzej Banburski; Xavier Boix; Jack Hidary (CoRR, 2018)

A Surprising Linear Relationship Predicts Test Performance in Deep Networks. - Qianli Liao; Brando Miranda; Andrzej Banburski; Jack Hidary; Tomaso A. Poggio (CoRR, 2018)

Quantum Computing: An Applied Approach - Jack Hidary (Springer, 2019)

Theory III: Dynamics and Generalization in Deep Networks. - Andrzej Banburski; Qianli Liao; Brando Miranda; Lorenzo Rosasco; Bob Liang; Jack Hidary; Tomaso A. Poggio (CoRR, 2019)

TensorNetwork: A Library for Physics and Machine Learning. - Chase Roberts; Ashley Milsted; Martin Ganahl; Adam Zalcman; Bruce Fontaine; Yijian Zou; Jack Hidary; Guifre Vidal; Stefan Leichenauer (CoRR, 2019)

TensorNetwork on TensorFlow: A Spin Chain Application Using Tree Tensor Networks. - Ashley Milsted; Martin Ganahl; Stefan Leichenauer; Jack Hidary; Guifre Vidal (CoRR, 2019)

TensorNetwork for Machine Learning. - Stavros Efthymiou; Jack Hidary; Stefan Leichenauer (CoRR, 2019)

Quantum Graph Neural Networks. - Guillaume Verdon; Trevor McCourt; Enxhell Luzhnica; Vikash Singh; Stefan Leichenauer; Jack Hidary (CoRR, 2019)

Quantum Hamiltonian-Based Models and the Variational Quantum Thermalizer Algorithm. - Guillaume Verdon; Jacob Marks; Sasha Nanda; Stefan Leichenauer; Jack Hidary (CoRR, 2019)

Transitioning organizations to post-quantum cryptography. - David Joseph; Rafael Misoczki; Marc Manzano; Joe Tricot; Fernando Dominguez Pinuaga; Olivier Lacombe; Stefan Leichenauer; Jack Hidary; Phil Venables; Royal Hansen (Nat., 2022)