Neural networks are a priori biased towards Boolean functions with low entropy. - Chris Mingard; Joar Skalse; Guillermo Valle Pérez; David Martínez-Rubio; Vladimir Mikulik; Ard A. Louis (CoRR, 2019)

The Equilibrium Hypothesis: Rethinking implicit regularization in Deep Neural Networks. - Yizhang Lou; Chris Mingard; Soufiane Hayou (CoRR, 2021)

Is SGD a Bayesian sampler? Well, almost. - Chris Mingard; Guillermo Valle Pérez; Joar Skalse; Ard A. Louis (J. Mach. Learn. Res., 2021)

Feature Learning and Signal Propagation in Deep Neural Networks. - Yizhang Lou; Chris E. Mingard; Soufiane Hayou (ICML, 2022)

Automatic Gradient Descent: Deep Learning without Hyperparameters. - Jeremy Bernstein; Chris Mingard; Kevin Huang; Navid Azizan; Yisong Yue (CoRR, 2023)

Do deep neural networks have an inbuilt Occam's razor? - Chris Mingard; Henry Rees; Guillermo Valle Pérez; Ard A. Louis (CoRR, 2023)

An exactly solvable model for emergence and scaling laws in the multitask sparse parity problem. - Yoonsoo Nam; Nayara Fonseca; Seok Hyeong Lee; Chris Mingard; Ard A. Louis (NeurIPS, 2024)

Exploiting the equivalence between quantum neural networks and perceptrons. - Chris Mingard; Jessica Pointing; Charles London; Yoonsoo Nam; Ard A. Louis (CoRR, 2024)

Visualising Feature Learning in Deep Neural Networks by Diagonalizing the Forward Feature Map. - Yoonsoo Nam; Chris Mingard; Seok Hyeong Lee; Soufiane Hayou; Ard A. Louis (CoRR, 2024)

Characterising the Inductive Biases of Neural Networks on Boolean Data. - Chris Mingard; Lukas Seier; Niclas Alexander Göring; Andrei-Vlad Badelita; Charles London; Ard A. Louis (CoRR, 2025)

Feature learning is decoupled from generalization in high capacity neural networks. - Niclas Alexander Göring; Charles London; Abdurrahman Hadi Erturk; Chris Mingard; Yoonsoo Nam; Ard A. Louis (CoRR, 2025)