Results 71 to 80 of about 165,261 (262)
Bayesian designs for hierarchical linear models [PDF]
, 2012 Two Bayesian optimal design criteria for hierarchical linear models are discussed – the ?? criterion for the estimation of individual-level parameters ?, and the ?? criterion for the estimation of hyperparameters ?.
Allenby, Gregory +5 more
core +1 more source
Hard‐Magnetic Soft Millirobots in Underactuated Systems
Advanced Robotics Research, EarlyView.This review provides a comprehensive overview of hard‐magnetic soft millirobots in underactuated systems. It examines key advances in structural design, physics‐informed modeling, and control strategies, while highlighting the interplay among these domains.
Qiong Wang +4 more
wiley +1 more source
BAYESIAN CURVE ESTIMATION BY MODEL AVERAGING [PDF]
A bayesian approach is used to estimate a nonparametric regression model. The main features of the procedure are, first, the functional form of the curve is approximated by a mixture of local polynomials by Bayesian Model Averaging (BMA); second, the ...
M. Dolores Redondas, Daniel Peña
core
Locally Adaptive Function Estimation for Binary Regression Models [PDF]
, 2003 In this paper we present a nonparametric Bayesian approach for fitting unsmooth or highly oscillating functions in regression models with binary responses. The approach extends previous work by Lang et al. (2002) for Gaussian responses.
Jerak, A. +3 more
core +1 more source
Advanced Robotics Research, EarlyView.Robots can learn manipulation tasks from human demonstrations. This work proposes a versatile method to identify the physical interactions that occur in a demonstration, such as sequences of different contacts and interactions with mechanical constraints.
Alex Harm Gert‐Jan Overbeek +3 more
wiley +1 more source
Continual Learning for Multimodal Data Fusion of a Soft Gripper
Advanced Robotics Research, EarlyView.Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley +1 more source
Bayesian Extreme Value Mixture Modelling for Estimating VaR [PDF]
A new extreme value mixture modelling approach for estimating Value-at-Risk (VaR) is proposed, overcoming the key issues of determining the threshold which defines the distribution tail and accounts for uncertainty due to threshold choice.
Les Oxley +3 more
core
Magnitude estimation in humans [PDF]
, 2013 Anyone who has climbed a mountain before knows that the perceived distance walked depends on more than just its physical length. This intriguing relationship between physical and experienced magnitudes has fascinated researchers across various ...
Petzschner, Frederike Hermi
core
Compliant Pneumatic Feet with Real‐Time Stiffness Adaptation for Humanoid Locomotion
Advanced Robotics Research, EarlyView.A compliant pneumatic foot with real‐time variable stiffness enables humanoid robots to adapt to changing terrains. Using onboard vision and pressure control, the foot modulates stiffness within each gait cycle, reducing impact forces and improving balance. The design, cast in soft silicone with embedded air chambers and Kevlar wrapping, offers durable,
Irene Frizza +3 more
wiley +1 more source
Bayesian Learning of Markov Network Structure
, 2006 We propose a simple and efficient approach to building undirected probabilistic classification models (Markov networks) that extend naive Bayes classifiers and outperform existing directed probabilistic classifiers (Bayesian networks) of similar ...
Rish, Irina +3 more
core +1 more source