Carl Edward Rasmussen

Name:	Carl Edward Rasmussen
Affiliation:	University of Cambridge
E-mail:	(only provided to users who are logged into talks.cam)
Last login:	12 Mar 2026, 1:51 p.m.

Public lists managed by Carl Edward Rasmussen

• Cambridge Ellis Unit
• Computational and Biological Learning Seminar Series
• Joint Machine Learning Seminars
• Machine Learning and Inference (One day meeting)
• Machine Learning @ CUED
• Machine Learning Reading Group @ CUED
• Probabilistic Numerics Reading Group

Talks given by Carl Edward Rasmussen

Obviously this only lists talks that are listed through talks.cam. Furthermore, this facility only works if the speaker's e-mail was specified in a talk. Most talks have not done this.

• Cooperative Mechanisms Against Climate Change
• Mechanisms Against Climate Change
• Variational Inference in Gaussian Processes for non-linear time series
• Inference in non-linear dynamical systems -- a machine learning perspective
• Learning to Control
• Inference in Gaussian Process models

Talks organised by Carl Edward Rasmussen

This list is based on what was entered into the 'organiser' field in a talk. It may not mean that Carl Edward Rasmussen actually organised the talk, they may have been responsible only for entering the talk into the talks.cam system.

• Modern Bayesian Experimental Design
• Prob Numerics 5 ch 11-13
• Online Meta-Learning
• Probabilistic modeling for position and orientation estimation using inertial sensors
• Data Driven Discrete Time Modeling of Continuous Time Nonlinear Systems: Problems, Challenges, Success Stories
• Efficient multi-task Gaussian process models for genome-wide association studies
• Factored Shapes and Appearances for Parts-based Object Understanding AND Transformation Equivariant Boltzmann Machines
• Optimal Reinforcement Learning for Gaussian Systems
• Connections between Gaussian Process Regression, Kalman filtering and RTS Smoothing
• Novi Quadrianto
• Motor Skills Learning for Robotics
• Convex Variational Bayesian Inference for Large Scale Generalized Linear Models
• Beam Sampling for Infinite Hidden Markov Models
• Clinical data based optimal STI strategies for HIV: a reinforcement learning approach
• Graph Kernels for Data Mining