Results 91 to 100 of about 3,284,626 (292)

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

Rock typing and causality analysis in unconventional formation using Bayes nets

Petroleum Research
Unconventional formations are characterized by high heterogeneity and anisotropy, making it difficult to interpret logging data, perform core analysis, and create accurate petrophysical models.
Evgeny Chekhonin, Alexander Nikitin, Dimitri Pissarenko, Yuri Popov, Raissa Romushkevich, Dzhulia Zagranovskaya   +5 more
doaj   +1 more source

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, Hiroshi Kaminaga, Philippe Fraisse, Gentiane Venture   +3 more
wiley   +1 more source

Bayesian Neural Networks

Journal of the Brazilian Computer Society, 1997
Bayesian techniques have been developed over many years in a range of different fields, but have only recently been applied to the problem of learning in neural networks. As well as providing a consistent framework for statistical pattern recognition, the Bayesian approach offers a number of practical advantages including a solution to the problem of ...
openaire   +4 more sources

Hybrid time Bayesian networks

International Journal of Approximate Reasoning, 2015
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Manxia Liu, Arjen Hommersom, Maarten van der Heijden, Peter J. F. Lucas   +3 more
openaire   +9 more sources

Confirmation and Reduction: A Bayesian Account [PDF]

, 2010
Various scientific theories stand in a reductive relation to each other. In a recent article, we have argued that a generalized version of the Nagel-Schaffner model (GNS) is the right account of this relation.
R. Frigg, Frigg, R., Dizadji-Bahmani, Foad, S. Hartmann, F. Dizadji-Bahmani, Hartmann, Stephan, Dizadji-Bahmani, F., Hartmann, S., Frigg, Roman   +8 more
core   +1 more source

Muscle Control of an Extra Robotic Digit

Advanced Robotics Research, EarlyView.
This study compares muscle‐ and movement‐based control for operating a supernumerary robotic thumb. While movement control performs better in the proposed tasks, muscle‐based (EMG) control promotes broader motor learning. The results highlight the promise and challenges of using biosignals for human augmentation, offering new insights into intuitive ...
Julien Russ, Lucy Dowdall, Francesco Cenciarelli, Kitty Goodridge, Mabel Ziman, Hristo Dimitrov, Danielle Clode, Tamar R. Makin   +7 more
wiley   +1 more source

Learning Large-Scale Bayesian Networks with the sparsebn Package

Journal of Statistical Software, 2019
Learning graphical models from data is an important problem with wide applications, ranging from genomics to the social sciences. Nowadays datasets often have upwards of thousands - sometimes tens or hundreds of thousands - of variables and far fewer
Bryon Aragam, Jiaying Gu, Qing Zhou
doaj   +1 more source

Mutual Adaptation and Influence: Review of Latent Dynamics Models in Human–Robot Interaction

Advanced Robotics Research, EarlyView.
Robots are becoming better teammates by learning hidden patterns in how people act. This review covers how state‐of‐the‐art approaches leverage these patterns to help robots not only react but also anticipate and guide cooperation. Here, we synthesize a unifying framework for these approaches, classify and review existing works, and highlight key ...
Mason O. Smith, Sunny Amatya, Seyed Yousef Soltanian, Jonathan Bush, Wenlong Zhang   +4 more
wiley   +1 more source

Modular network construction using eQTL data: an analysis of computational costs and benefits

Frontiers in Genetics, 2014
Background: In this paper, we consider analytic methods for the integrated analysis of genomic DNA variation and mRNA expression (also named as eQTL data), to discover genetic networks that are associated with a complex trait of interest.
Yen-Yi eHo, Leslie Michael Cope, Giovanni eParmigiani   +2 more
doaj   +1 more source