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Michael A. Osborne

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Papers (29)

  1. A Physics-Inspired Optimizer: Velocity Regularized Adam cs.LG · 2025 · author #4
  2. Automated Model Selection with Bayesian Quadrature cs.LG · 2019 · author #4
  3. Asynchronous Batch Bayesian Optimisation with Improved Local Penalisation stat.ML · 2019 · author #5
  4. Rejoinder for "Probabilistic Integration: A Role in Statistical Computation?" stat.CO · 2018 · author #4
  5. Fingerprint Policy Optimisation for Robust Reinforcement Learning cs.LG · 2018 · author #2
  6. Optimization, fast and slow: optimally switching between local and Bayesian optimization stat.ML · 2018 · author #2
  7. Quantum algorithms for training Gaussian Processes quant-ph · 2018 · author #3
  8. Bayesian Optimization for Dynamic Problems stat.ML · 2018 · author #2
  9. Spatial Field Reconstruction and Sensor Selection in Heterogeneous Sensor Networks with Stochastic Energy Harvesting eess.SP · 2018 · author #5
  10. Gaussian Process Regression for In-situ Capacity Estimation of Lithium-ion Batteries stat.AP · 2017 · author #3
  11. Fast Information-theoretic Bayesian Optimisation stat.ML · 2017 · author #4
  12. Bayesian Optimization for Probabilistic Programs stat.ML · 2017 · author #4
  13. Distributionally Ambiguous Optimization Techniques for Batch Bayesian Optimization stat.ML · 2017 · author #2
  14. A Novel Approach to Forecasting Financial Volatility with Gaussian Process Envelopes stat.ML · 2017 · author #3
  15. Distribution of Gaussian Process Arc Lengths stat.ML · 2017 · author #3
  16. Gaussian process regression for forecasting battery state of health stat.AP · 2017 · author #2
  17. Practical Bayesian Optimization for Variable Cost Objectives stat.ML · 2017 · author #2
  18. Alternating Optimisation and Quadrature for Robust Control cs.LG · 2016 · author #5
  19. Preconditioning Kernel Matrices stat.ML · 2016 · author #2
  20. Probabilistic Integration: A Role in Statistical Computation? stat.ML · 2015 · author #4
  21. A Variational Bayesian State-Space Approach to Online Passive-Aggressive Regression stat.ML · 2015 · author #3
  22. A Gaussian process framework for modelling stellar activity signals in radial velocity data astro-ph.EP · 2015 · author #3
  23. Frank-Wolfe Bayesian Quadrature: Probabilistic Integration with Theoretical Guarantees stat.ML · 2015 · author #4
  24. Sampling for Inference in Probabilistic Models with Fast Bayesian Quadrature stat.ML · 2014 · author #2
  25. Variational Inference for Gaussian Process Modulated Poisson Processes stat.ML · 2014 · author #3
  26. Raiders of the Lost Architecture: Kernels for Bayesian Optimization in Conditional Parameter Spaces stat.ML · 2014 · author #5
  27. Efficient Bayesian Nonparametric Modelling of Structured Point Processes stat.ML · 2014 · author #3
  28. Active Learning of Linear Embeddings for Gaussian Processes stat.ML · 2013 · author #2
  29. A Kernel for Hierarchical Parameter Spaces stat.ML · 2013 · author #2

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