Ben Adlam
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Underspecification presents challenges for credibility in modern machine learning
A D'Amour, K Heller, D Moldovan, B Adlam, B Alipanahi, A Beutel, ...
Journal of Machine Learning Research 23 (226), 1-61, 2022
Crowding and the shape of COVID-19 epidemics
B Rader, SV Scarpino, A Nande, AL Hill, B Adlam, RC Reiner, DM Pigott, ...
Nature Medicine, 1-6, 2020
Finite Versus Infinite Neural Networks: an Empirical Study
J Lee, S Schoenholz, J Pennington, B Adlam, L Xiao, R Novak, ...
Advances in Neural Information Processing Systems, 2020
Current CRISPR gene drive systems are likely to be highly invasive in wild populations
C Noble, B Adlam, GM Church, KM Esvelt, MA Nowak
Elife 7, e33423, 2018
The Neural Tangent Kernel in High Dimensions: Triple Descent and a Multi-Scale Theory of Generalization
B Adlam, J Pennington
Thirty-seventh International Conference on Machine Learning, 2020
Dynamics of COVID-19 under social distancing measures are driven by transmission network structure
A Nande, B Adlam, J Sheen, MZ Levy, AL Hill
PLoS computational biology 17 (2), e1008684, 2021
Understanding Double Descent Requires a Fine-Grained Bias-Variance Decomposition
B Adlam, J Pennington
Advances in Neural Information Processing Systems, 2020
The effect of eviction moratoria on the transmission of SARS-CoV-2
ALH Anjalika Nande, Justin Sheen, Emma L Walters, Brennan Klein, Matteo ...
Nature Communications 12 (2274), 2021
Amplifiers of selection
B Adlam, K Chatterjee, MA Nowak
Proceedings of the Royal Society A: Mathematical, Physical and Engineering …, 2015
The Surprising Simplicity of the Early-Time Learning Dynamics of Neural Networks
W Hu, L Xiao, B Adlam, J Pennington
Advances in Neural Information Processing Systems, 2020
Universality of fixation probabilities in randomly structured populations
B Adlam, MA Nowak
Scientific Reports 4 (1), 6692, 2014
The time scale of evolutionary innovation
K Chatterjee, A Pavlogiannis, B Adlam, MA Nowak
PLoS computational biology 10 (9), e1003818, 2014
Overparameterization improves robustness to covariate shift in high dimensions
N Tripuraneni, B Adlam, J Pennington
Advances in Neural Information Processing Systems 34, 13883-13897, 2021
A Random Matrix Perspective on Mixtures of Nonlinearities in High Dimensions
B Adlam, J Levinson, J Pennington
International Conference on Artificial Intelligence and Statistics, 2022
Beyond human data: Scaling self-training for problem-solving with language models
A Singh, JD Co-Reyes, R Agarwal, A Anand, P Patil, PJ Liu, J Harrison, ...
arXiv preprint arXiv:2312.06585, 2023
Covariate shift in high-dimensional random feature regression
N Tripuraneni, B Adlam, J Pennington
arXiv preprint arXiv:2111.08234, 2021
Adanet: A scalable and flexible framework for automatically learning ensembles
C Weill, J Gonzalvo, V Kuznetsov, S Yang, S Yak, H Mazzawi, E Hotaj, ...
arXiv preprint arXiv:1905.00080, 2019
Spectral statistics of sparse random graphs with a general degree distribution
B Adlam, Z Che
arXiv preprint arXiv:1509.03368, 2015
Homogenization of SGD in high-dimensions: Exact dynamics and generalization properties
C Paquette, E Paquette, B Adlam, J Pennington
arXiv preprint arXiv:2205.07069, 2022
Cold Posteriors and Aleatoric Uncertainty
B Adlam, J Snoek, SL Smith
ICML Workshop on Uncertainty & Robustness in Deep Learning, 2020
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