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Ard A. Louis
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2020 – today
- 2024
- [j5]Kamaludin Dingle, Mohammad Alaskandarani, Boumediene Hamzi, Ard A. Louis:
Exploring Simplicity Bias in 1D Dynamical Systems. Entropy 26(5): 426 (2024) - [c2]Ouns El Harzli, Bernardo Cuenca Grau, Guillermo Valle Pérez, Ard A. Louis:
Double-Descent Curves in Neural Networks: A New Perspective Using Gaussian Processes. AAAI 2024: 11856-11864 - [i10]Yoonsoo Nam, Nayara Fonseca, Seok Hyeong Lee, Ard A. Louis:
An exactly solvable model for emergence and scaling laws. CoRR abs/2404.17563 (2024) - [i9]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) - 2023
- [i8]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) - 2021
- [j4]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) - [i7]Ouns El Harzli, Guillermo Valle Pérez, Ard A. Louis:
Double-descent curves in neural networks: a new perspective using Gaussian processes. CoRR abs/2102.07238 (2021) - [i6]Shuofeng Zhang, Isaac Reid, Guillermo Valle Pérez, Ard A. Louis:
Why Flatness Correlates With Generalization For Deep Neural Networks. CoRR abs/2103.06219 (2021) - 2020
- [i5]Chris Mingard, Guillermo Valle Pérez, Joar Skalse, Ard A. Louis:
Is SGD a Bayesian sampler? Well, almost. CoRR abs/2006.15191 (2020) - [i4]Guillermo Valle Pérez, Ard A. Louis:
Generalization bounds for deep learning. CoRR abs/2012.04115 (2020)
2010 – 2019
- 2019
- [j3]Antonio Suma, Erik Poppleton, Michael Matthies, Petr Sulc, Flavio Romano, Ard A. Louis, Jonathan P. K. Doye, Cristian Micheletti, Lorenzo Rovigatti:
TacoxDNA: A user-friendly web server for simulations of complex DNA structures, from single strands to origami. J. Comput. Chem. 40(29): 2586-2595 (2019) - [c1]Guillermo Valle Pérez, Chico Q. Camargo, Ard A. Louis:
Deep learning generalizes because the parameter-function map is biased towards simple functions. ICLR (Poster) 2019 - [i3]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) - 2018
- [i2]Guillermo Valle Pérez, Chico Q. Camargo, Ard A. Louis:
Deep learning generalizes because the parameter-function map is biased towards simple functions. CoRR abs/1805.08522 (2018) - 2016
- [j2]Sam F. Greenbury, Steffen Schaper, Sebastian E. Ahnert, Ard A. Louis:
Genetic Correlations Greatly Increase Mutational Robustness and Can Both Reduce and Enhance Evolvability. PLoS Comput. Biol. 12(3) (2016) - 2014
- [j1]Petr Sulc, Thomas E. Ouldridge, Flavio Romano, Jonathan P. K. Doye, Ard A. Louis:
Simulating a burnt-bridges DNA motor with a coarse-grained DNA model. Nat. Comput. 13(4): 535-547 (2014) - 2013
- [i1]Hector Zenil, Fernando Soler-Toscano, Kamaludin Dingle, Ard A. Louis:
Graph Automorphism and Topological Characterization of Synthetic and Natural Complex Networks by Information Content. CoRR abs/1306.0322 (2013)
Coauthor Index
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