Rasmussen, Carl Edward

35 publications

TMLR 2024 Integrated Variational Fourier Features for Fast Spatial Modelling with Gaussian Processes Talay M Cheema, Carl Edward Rasmussen

JMLR 2024 Numerically Stable Sparse Gaussian Processes via Minimum Separation Using Cover Trees Alexander Terenin, David R. Burt, Artem Artemev, Seth Flaxman, Mark van der Wilk, Carl Edward Rasmussen, Hong Ge

NeurIPS 2022 Sparse Gaussian Process Hyperparameters: Optimize or Integrate? Vidhi Lalchand, Wessel Bruinsma, David Burt, Carl Edward Rasmussen

NeurIPS 2021 Kernel Identification Through Transformers Fergus Simpson, Ian Davies, Vidhi Lalchand, Alessandro Vullo, Nicolas Durrande, Carl Edward Rasmussen

NeurIPS 2021 Marginalised Gaussian Processes with Nested Sampling Fergus Simpson, Vidhi Lalchand, Carl Edward Rasmussen

JMLR 2020 Convergence of Sparse Variational Inference in Gaussian Processes Regression David R. Burt, Carl Edward Rasmussen, Mark van der Wilk

AISTATS 2020 Deep Structured Mixtures of Gaussian Processes Martin Trapp, Robert Peharz, Franz Pernkopf, Carl Edward Rasmussen

NeurIPS 2020 Ensembling Geophysical Models with Bayesian Neural Networks Ushnish Sengupta, Matt Amos, Scott Hosking, Carl Edward Rasmussen, Matthew Juniper, Paul Young

ICLR 2019 Deep Convolutional Networks as Shallow Gaussian Processes Adrià Garriga-Alonso, Carl Edward Rasmussen, Laurence Aitchison

ICML 2019 Overcoming Mean-Field Approximations in Recurrent Gaussian Process Models Alessandro Davide Ialongo, Mark Van Der Wilk, James Hensman, Carl Edward Rasmussen

ICML 2019 Rates of Convergence for Sparse Variational Gaussian Process Regression David Burt, Carl Edward Rasmussen, Mark Van Der Wilk

ICML 2018 PIPPS: Flexible Model-Based Policy Search Robust to the Curse of Chaos Paavo Parmas, Carl Edward Rasmussen, Jan Peters, Kenji Doya

NeurIPS 2017 Convolutional Gaussian Processes Mark van der Wilk, Carl Edward Rasmussen, James Hensman

NeurIPS 2017 Data-Efficient Reinforcement Learning in Continuous State-Action Gaussian-POMDPs Rowan McAllister, Carl Edward Rasmussen

NeurIPS 2016 Understanding Probabilistic Sparse Gaussian Process Approximations Matthias Bauer, Mark van der Wilk, Carl Edward Rasmussen

NeurIPS 2014 Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models Yarin Gal, Mark van der Wilk, Carl Edward Rasmussen

NeurIPS 2014 Variational Gaussian Process State-Space Models Roger Frigola, Yutian Chen, Carl Edward Rasmussen

NeurIPS 2013 Bayesian Inference and Learning in Gaussian Process State-Space Models with Particle MCMC Roger Frigola, Fredrik Lindsten, Thomas B Schön, Carl Edward Rasmussen

ICML 2011 PILCO: A Model-Based and Data-Efficient Approach to Policy Search Marc Peter Deisenroth, Carl Edward Rasmussen

ICML 2010 Gaussian Process Change Point Models Yunus Saatci, Ryan D. Turner, Carl Edward Rasmussen

MLOSS 2010 Gaussian Processes for Machine Learning (GPML) Toolbox Carl Edward Rasmussen, Hannes Nickisch

JMLR 2010 Sparse Spectrum Gaussian Process Regression Miguel Lázaro-Gredilla, Joaquin Quiñnero-Candela, Carl Edward Rasmussen, Aníbal R. Figueiras-Vidal

JMLR 2008 Approximations for Binary Gaussian Process Classification Hannes Nickisch, Carl Edward Rasmussen

JMLR 2007 The Need for Open Source Software in Machine Learning Sören Sonnenburg, Mikio L. Braun, Cheng Soon Ong, Samy Bengio, Leon Bottou, Geoffrey Holmes, Yann LeCun, Klaus-Robert Müller, Fernando Pereira, Carl Edward Rasmussen, Gunnar Rätsch, Bernhard Schölkopf, Alexander Smola, Pascal Vincent, Jason Weston, Robert Williamson

ICML 2006 A Choice Model with Infinitely Many Latent Features Dilan Görür, Frank Jäkel, Carl Edward Rasmussen

JMLR 2005 A Unifying View of Sparse Approximate Gaussian Process Regression Joaquin Quiñonero-Candela, Carl Edward Rasmussen

JMLR 2005 Assessing Approximate Inference for Binary Gaussian Process Classification Malte Kuss, Carl Edward Rasmussen

ICML 2005 Healing the Relevance Vector Machine Through Augmentation Carl Edward Rasmussen, Joaquin Quiñonero Candela

NeurIPS 2002 Gaussian Process Priors with Uncertain Inputs Application to Multiple-Step Ahead Time Series Forecasting Agathe Girard, Carl Edward Rasmussen, Joaquin Quiñonero Candela, Roderick Murray-Smith

NeurIPS 2000 Occam's Razor Carl Edward Rasmussen, Zoubin Ghahramani

NeurIPS 1999 Bayesian Modelling of fMRI Lime Series Pedro A. d. F. R. Højen-Sørensen, Lars Kai Hansen, Carl Edward Rasmussen

NeurIPS 1999 The Infinite Gaussian Mixture Model Carl Edward Rasmussen

NeurIPS 1995 A Practical Monte Carlo Implementation of Bayesian Learning Carl Edward Rasmussen

NeurIPS 1995 Gaussian Processes for Regression Christopher K. I. Williams, Carl Edward Rasmussen

NeCo 1994 Pruning from Adaptive Regularization Lars Kai Hansen, Carl Edward Rasmussen