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 | 666 | 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 | 283* | 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 | 183 | 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 | 171 | 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 | 119 | 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 | 100 | 2021 |
Understanding Double Descent Requires a Fine-Grained Bias-Variance Decomposition B Adlam, J Pennington Advances in Neural Information Processing Systems, 2020 | 97 | 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 | 90 | 2021 |
Amplifiers of selection B Adlam, K Chatterjee, MA Nowak Proceedings of the Royal Society A: Mathematical, Physical and Engineering …, 2015 | 73 | 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 | 65 | 2020 |
Universality of fixation probabilities in randomly structured populations B Adlam, MA Nowak Scientific Reports 4 (1), 6692, 2014 | 46 | 2014 |
The time scale of evolutionary innovation K Chatterjee, A Pavlogiannis, B Adlam, MA Nowak PLoS computational biology 10 (9), e1003818, 2014 | 45 | 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 | 40 | 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 | 32* | 2022 |
Covariate shift in high-dimensional random feature regression N Tripuraneni, B Adlam, J Pennington arXiv preprint arXiv:2111.08234, 2021 | 23 | 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 | 21 | 2019 |
Spectral statistics of sparse random graphs with a general degree distribution B Adlam, Z Che arXiv preprint arXiv:1509.03368, 2015 | 19* | 2015 |
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 | 17 | 2023 |
Exploring the Uncertainty Properties of Neural Networks’ Implicit Priors in the Infinite-Width Limit B Adlam, J Lee, L Xiao, J Pennington, Snoek, Jasper The Ninth International Conference on Learning Representations, 2021 | 17 | 2021 |
Cold Posteriors and Aleatoric Uncertainty B Adlam, J Snoek, SL Smith ICML Workshop on Uncertainty & Robustness in Deep Learning, 2020 | 16 | 2020 |