Results 131 to 140 of about 371,316 (301)

Supplemental Materials to Bayesian Methods for Data Analysis, 3rd Edition

, 2018
These files are the supplemental materials referred to in the 3rd edition of Bayesian Methods for Data Analysis. This record is complete with datasets, R code, and WinBUGS. There is a csv file that provides a map for page number and associated file.
Carlin, Bradley P, Louis, Thomas A
core   +1 more source

3D Printing of Soft Robotic Systems: Advances in Fabrication Strategies and Future Trends

Advanced Robotics Research, EarlyView.
Collectively, this review systematically examines 3D‐printed soft robotics, encompassing material selections, function integration, and manufacturing methodologies. Meanwhile, fabrication strategies are analyzed in order of increasing complexity, highlighting persistent challenges with proposed solutions.
Changjiang Liu, Bin Cui, Xumin Huang, Xiaoyu (Rayne) Zheng, T. Thang Vo‐Doan, Ruirui Qiao   +5 more
wiley   +1 more source

Inverse Bayesian Methods for Groundwater Vulnerability Assessment

Physical Sciences Forum
Groundwater vulnerability assessment (GVA) is critical for understanding contaminant migration into groundwater systems, yet conventional methods often overlook its probabilistic nature.
Nasrin Taghavi, Robert K. Niven, Matthias Kramer, David J. Paull   +3 more
doaj   +1 more source

Identifying Physical Interactions in Contact‐Based Robot Manipulation for Learning from Demonstration

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, Herman van der Kooij, Douwe Dresscher, Mark Vlutters   +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

Federated Bayesian Deep Learning: The Application of Statistical Aggregation Methods to Bayesian Models

IEEE Access
Federated learning (FL) is an approach to training machine learning models that takes advantage of multiple distributed datasets while maintaining data privacy and reducing communication costs associated with sharing local datasets.
John Fischer, Marko Orescanin, Justin Loomis, Patrick Mcclure   +3 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

Computational methods for Bayesian model choice

, 2009
12 pages, 4 figures, submitted for the proceedings of MaxEnt 2009In this note, we shortly survey some recent approaches on the approximation of the Bayes factor used in Bayesian hypothesis testing and in Bayesian model choice.
Chun-Yong Chan, Robert, C.P., C. P. Robert, D. Wraith, Wraith, D., Paul M. Goggans, Robert, Christian P., Wraith, Darren, Robert, Christian   +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

Bayesian methods: a potential path forward for sepsis trials. [PDF]

Crit Care, 2023
Tomlinson G, Al-Khafaji A, Conrad SA, Factora FNF, Foster DM, Galphin C, Gunnerson KJ, Khan S, Kohli-Seth R, McCarthy P, Meena NK, Pearl RG, Rachoin JS, Rains R, Seneff M, Tidswell M, Walker PM, Kellum JA.   +17 more
europepmc   +1 more source