Learning invariances in neural networks from training data G Benton, M Finzi, P Izmailov, AG Wilson Advances in neural information processing systems 33, 17605-17616, 2020 | 136 | 2020 |
Loss surface simplexes for mode connecting volumes and fast ensembling G Benton, W Maddox, S Lotfi, AGG Wilson International Conference on Machine Learning, 769-779, 2021 | 56 | 2021 |
Bayesian model selection, the marginal likelihood, and generalization S Lotfi, P Izmailov, G Benton, M Goldblum, AG Wilson International Conference on Machine Learning, 14223-14247, 2022 | 50 | 2022 |
Rethinking parameter counting in deep models: Effective dimensionality revisited WJ Maddox, G Benton, AG Wilson arXiv preprint arXiv:2003.02139, 2020 | 50 | 2020 |
Residual pathway priors for soft equivariance constraints M Finzi, G Benton, AG Wilson Advances in Neural Information Processing Systems 34, 30037-30049, 2021 | 38 | 2021 |
Function-space distributions over kernels G Benton, WJ Maddox, J Salkey, J Albinati, AG Wilson Advances in Neural Information Processing Systems 32, 2019 | 36 | 2019 |
Trajectory based podcast recommendation G Benton, G Fazelnia, A Wang, B Carterette arXiv preprint arXiv:2009.03859, 2020 | 6 | 2020 |
Volatility based kernels and moving average means for accurate forecasting with gaussian processes G Benton, W Maddox, AG Wilson International Conference on Machine Learning, 1798-1816, 2022 | 4 | 2022 |
Deep Probabilistic Time Series Forecasting over Long Horizons G Benton, N Gruver, W Maddox, AG Wilson | 1 | 2022 |
Function Space Reasoning for Gaussian Processes and Neural Networks G Benton New York University, 2023 | | 2023 |
Rethinking Parameter Counting: Effective Dimensionality Revisited G Benton, W Maddox, AG Wilson | | 2020 |
Modified Kernel Density Estimators for Gridded Estimation of Precipitation Climatologies G Benton University of Colorado at Boulder, 2018 | | 2018 |
Supplementary Materials for Function-Space Distributions over Kernels GW Benton, WJ Maddox, JP Salkey, J Albinati, AG Wilson | | |