Portfolio item number 1
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Posts by Collection
portfolio
Portfolio item number 2
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publications
Neural Linear Models with Functional Gaussian Process Priors
Published in Advances in Approximate Bayesian Inference 2020, 1900
Latent Derivative Bayesian Last Layer Networks
Published in International Conference on Artificial Intelligence and Statistics 2021, 1900
Function-Space Regularization for Deep Bayesian Classification
Published in Advances in Approximate Bayesian Inference 2023, 1900
Online Laplace Model Selection Revisited
Published in Advances in Approximate Bayesian Inference 2023, 1900
Beyond Intuition, a Framework for Applying GPs to Real-World Data
Published in Structured Probabilistic Inference & Generative Modeling Workshop at ICML 2023, 1900
Minimal Random Code Learning with Mean-KL Parameterization
Published in Neural Compression Workshop at ICML 2023, 1900
Sampling from Gaussian Process Posteriors using Stochastic Gradient Descent
Published in Advances in Neural Information Processing Systems 2023, 1900
Stochastic Gradient Descent for Gaussian Processes Done Right
Published in International Conference on Learning Representations 2024, 1900
Warm Start Marginal Likelihood Optimisation for Iterative Gaussian Processes
Published in Advances in Approximate Bayesian Inference 2024, 1900
Improving Linear System Solvers for Hyperparameter Optimisation in Iterative Gaussian Processes
Published in Advances in Neural Information Processing Systems 2024, 1900
Scaling Gaussian Processes for Learning Curve Prediction via Latent Kronecker Structure
Published in Bayesian Decision-making and Uncertainty Workshop at NeurIPS 2024, 1900
Scalable Gaussian Processes with Latent Kronecker Structure
Published in International Conference on Machine Learning 2025, 1900
talks
Talk 1 on Relevant Topic in Your Field
Published:
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Conference Proceeding talk 3 on Relevant Topic in Your Field
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teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
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Teaching experience 2
Workshop, University 1, Department, 2015
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