 Theoretical characterisation of the Gauss-Newton conditioning in Neural NetworksNeural Information Processing Systems (NeurIPS), 2024 |
 Optimising Distributions with Natural Gradient SurrogatesInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023 |
 MKOR: Momentum-Enabled Kronecker-Factor-Based Optimizer Using Rank-1
UpdatesNeural Information Processing Systems (NeurIPS), 2023 |
 Achieving High Accuracy with PINNs via Energy Natural GradientsInternational Conference on Machine Learning (ICML), 2023 |
 Rethinking Gauss-Newton for learning over-parameterized modelsNeural Information Processing Systems (NeurIPS), 2023 |
 Gradient Descent on Neurons and its Link to Approximate Second-Order
OptimizationInternational Conference on Machine Learning (ICML), 2022 |
