PHYSICAL REVIEW A 92, Quantum theory of a bandpass Purcell filter for qubit readout Eyob A. Sete,1,* John M. Martinis,2,3 and Alexander N. Korotkov1 1

Source URL: www.ee.ucr.edu

1 Nonlinear Ego-Motion Estimation from Optical Flow for Online Control of a Quadrotor UAV Volker Grabe, Heinrich H. B¨ulthoff, Davide Scaramuzza, and Paolo Robuffo Giordano

Source URL: rpg.ifi.uzh.ch

• Control theory
• Robot control
• Classical mechanics
• Rotational symmetry
• Physical quantities
• Extended Kalman filter
• Homography
• Kalman filter
• Kinematics
• Angular velocity
• Damping
• Optical flow

Journal of Machine Learning Research–1959 Submitted 10/05; PublishedA Unifying View of Sparse Approximate Gaussian Process Regression

Source URL: jmlr.org

• Mathematical analysis
• Statistical theory
• Probability theory
• Normal distribution
• Stable distributions
• Multivariate normal distribution
• Regression analysis
• Gaussian process
• Kalman filter

Decentralized Detection and Classification using Kernel Methods XuanLong Nguyen XUANLONG @ CS . BERKELEY. EDU Martin J. Wainwright WAINWRIG @ EECS . BERKELEY. EDU

Source URL: dept.stat.lsa.umich.edu

• Operator theory
• Mathematics
• Statistical classification
• Algebra
• Distribution
• Number theory
• Positive-definite kernel
• Support vector machine
• Mathematical analysis
• operator
• Kalman filter

An Evaluation of Models for Predicting Opponent Positions in First-Person Shooter Video Games Stephen Hladky and Vadim Bulitko filters to predict opponent positions in first-person shooter (FPS) video games. These models

Source URL: www.csse.uwa.edu.au

• Statistics
• Monte Carlo methods
• Probability theory
• Estimation theory
• Robot control
• Nonparametric statistics
• Markov models
• Particle filter
• Prediction
• Hidden semi-Markov model
• Resampling
• Markov chain

C:/Users/Jur van den Berg/Documents/papers/RSS10 - NeedleSteering/jur-planningcontrol.dvi

Source URL: goldberg.berkeley.edu

• Control theory
• Robot control
• Stochastic control
• Robot kinematics
• Optimal control
• Motion planning
• Kalman filter
• Linear-quadratic-Gaussian control
• Robotics
• Robot
• Normal distribution

Scaling up Gaussian Belief Space Planning through Covariance-Free Trajectory Optimization and Automatic Differentiation Sachin Patil, Gregory Kahn, Michael Laskey, John Schulman, Ken Goldberg, Pieter Abbeel University of

Source URL: goldberg.berkeley.edu

• Mathematical optimization
• Systems theory
• Engineering
• Systems science
• Control theory
• Robot control
• Operations research
• Optimal control
• Trajectory optimization
• Kalman filter
• Model predictive control
• Quadratic programming

A Simple Sequential Algorithm for Approximating Bayesian Inference Elizabeth Bonawitz, Stephanie Denison, Annie Chen, Alison Gopnik, & Thomas L. Griffiths {liz b, smdeniso, c annie, gopnik, tom griffiths}@berkeley.edu De

Source URL: ccdlab.rutgers.edu

• Statistics
• Sampling techniques
• Statistical mechanics
• Stochastic simulation
• Statistical theory
• Statistical inference
• Bayesian inference
• Bayesian network
• Particle filter
• Bayesian probability
• Monte Carlo method
• Bayesian statistics

Nonparametric Tree Graphical Models via Kernel Embeddings 1 Le Song,1 Arthur Gretton,1,2 Carlos Guestrin1 School of Computer Science, Carnegie Mellon University; 2 MPI for Biological Cybernetics

Source URL: select.cs.cmu.edu

• Mathematics
• Mathematical analysis
• Hilbert space
• Topology
• Probability theory
• Model theory
• Graphical models
• Reproducing kernel Hilbert space
• Positive-definite kernel
• Embedding
• Belief propagation
• Kalman filter

Online Self-Calibration for Robotic Systems J´erˆome Maye, Hannes Sommer, Gabriel Agamennoni, Roland Siegwart, and Paul Furgale Autonomous Systems Lab, ETH Zurich, Switzerland email: {jerome.maye, hannes.sommer, gabrie

Source URL: europa2.informatik.uni-freiburg.de

• Statistics
• Estimation theory
• Algebra
• Regression analysis
• Mathematics
• Parametric statistics
• Least squares
• Linear filters
• Fisher information
• Kalman filter
• Matrix
• Calibration