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Chris Mingard
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2020 – today
- 2024
- [i7]Chris Mingard, Jessica Pointing, Charles London, Yoonsoo Nam, Ard A. Louis:
Exploiting the equivalence between quantum neural networks and perceptrons. CoRR abs/2407.04371 (2024) - [i6]Yoonsoo Nam, Chris Mingard, Seok Hyeong Lee, Soufiane Hayou, Ard A. Louis:
Visualising Feature Learning in Deep Neural Networks by Diagonalizing the Forward Feature Map. CoRR abs/2410.04264 (2024) - 2023
- [i5]Jeremy Bernstein, Chris Mingard, Kevin Huang, Navid Azizan
, Yisong Yue:
Automatic Gradient Descent: Deep Learning without Hyperparameters. CoRR abs/2304.05187 (2023) - [i4]Chris Mingard, Henry Rees, Guillermo Valle Pérez, Ard A. Louis:
Do deep neural networks have an inbuilt Occam's razor? CoRR abs/2304.06670 (2023) - 2022
- [c1]Yizhang Lou, Chris E. Mingard, Soufiane Hayou:
Feature Learning and Signal Propagation in Deep Neural Networks. ICML 2022: 14248-14282 - 2021
- [j1]Chris Mingard, Guillermo Valle Pérez, Joar Skalse, Ard A. Louis:
Is SGD a Bayesian sampler? Well, almost. J. Mach. Learn. Res. 22: 79:1-79:64 (2021) - [i3]Yizhang Lou, Chris Mingard, Soufiane Hayou:
The Equilibrium Hypothesis: Rethinking implicit regularization in Deep Neural Networks. CoRR abs/2110.11749 (2021) - 2020
- [i2]Chris Mingard, Guillermo Valle Pérez, Joar Skalse, Ard A. Louis:
Is SGD a Bayesian sampler? Well, almost. CoRR abs/2006.15191 (2020)
2010 – 2019
- 2019
- [i1]Chris Mingard, Joar Skalse, Guillermo Valle Pérez, David Martínez-Rubio, Vladimir Mikulik, Ard A. Louis:
Neural networks are a priori biased towards Boolean functions with low entropy. CoRR abs/1909.11522 (2019)
Coauthor Index
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