Carl E. Rasmussen

20 papers A* 1A 1C 2Journal 10Unranked 5

Year	Rank	Type	Title / Venue / Authors
2022	J	`jnl`	Sparse Gaussian Process Hyperparameters: Optimize or Integrate? CoRR Vidhi Lalchand, Wessel P. Bruinsma, David R. Burt, Carl E. Rasmussen
2021	J	`jnl`	Kernel Identification Through Transformers. CoRR Fergus Simpson, Ian Davies, Vidhi Lalchand, Alessandro Vullo, Nicolas Durrande, Carl E. Rasmussen
2021	J	`jnl`	The Promises and Pitfalls of Deep Kernel Learning. CoRR Sebastian W. Ober, Carl E. Rasmussen, Mark van der Wilk
2021	A	`conf`	The promises and pitfalls of deep kernel learning. UAI Sebastian W. Ober, Carl E. Rasmussen, Mark van der Wilk
2019	J	`jnl`	Deep Structured Mixtures of Gaussian Processes. CoRR Martin Trapp, Robert Peharz, Franz Pernkopf, Carl E. Rasmussen
2019	J	`jnl`	Rates of Convergence for Sparse Variational Gaussian Process Regression. CoRR David R. Burt, Carl E. Rasmussen, Mark van der Wilk
2018	J	`jnl`	Learning Deep Mixtures of Gaussian Process Experts Using Sum-Product Networks. CoRR Martin Trapp, Robert Peharz, Carl E. Rasmussen, Franz Pernkopf
2018	—	`conf`	Nonlinear Set Membership Regression with Adaptive Hyper-Parameter Estimation for Online Learning and Control. ECC Jan-Peter Calliess, Stephen J. Roberts, Carl E. Rasmussen, Jan M. Maciejowski
2014	—	`conf`	Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models. NIPS Yarin Gal, Mark van der Wilk, Carl E. Rasmussen
2014	J	`jnl`	Distributed Variational Inference in Sparse Gaussian Process Regression and Latent Variable Models. CoRR Yarin Gal, Mark van der Wilk, Carl E. Rasmussen
2014	A*	`conf`	Policy search for learning robot control using sparse data. ICRA Bastian Bischoff, Duy Nguyen-Tuong, Herke van Hoof, Andrew McHutchon, Carl E. Rasmussen, Alois C. Knoll, Jan Peters, Marc Peter Deisenroth
2014	—	`conf`	Variational Gaussian Process State-Space Models. NIPS Roger Frigola, Yutian Chen, Carl E. Rasmussen
2014	J	`jnl`	Variational Gaussian Process State-Space Models. CoRR Roger Frigola, Yutian Chen, Carl E. Rasmussen
2013	—	`conf`	Bayesian Inference and Learning in Gaussian Process State-Space Models with Particle MCMC. NIPS Roger Frigola, Fredrik Lindsten, Thomas B. Schön, Carl E. Rasmussen
2013	J	`jnl`	Bayesian Inference and Learning in Gaussian Process State-Space Models with Particle MCMC. CoRR Roger Frigola, Fredrik Lindsten, Thomas B. Schön, Carl E. Rasmussen
2013	J	`jnl`	Identification of Gaussian Process State-Space Models with Particle Stochastic Approximation EM. CoRR Roger Frigola, Fredrik Lindsten, Thomas B. Schön, Carl E. Rasmussen
2012	—	`conf`	Active Learning of Model Evidence Using Bayesian Quadrature. NIPS Michael A. Osborne, David Duvenaud, Roman Garnett, Carl E. Rasmussen, Stephen J. Roberts, Zoubin Ghahramani
2008	C	`conf`	Approximate dynamic programming with Gaussian processes. ACC Marc Peter Deisenroth, Jan Peters, Carl E. Rasmussen
2004	C	`conf`	Gaussian process model based predictive control. ACC Jus Kocijan, Roderick Murray-Smith, Carl E. Rasmussen, Agathe Girard
1997	—	`—`	Evaluation of Gaussian processes and other methods for non-linear regression. Carl E. Rasmussen