Results 111 to 120 of about 864,389 (286)

Model seçiminde Bayesian yaklaşım

Ankara Universitesi Egitim Bilimleri Fakultesi Dergisi, 1995
Bu calismanin temel amaci Bayesian yaklasimim sosyal bilim arastirmalari model secimi iceriginde tanitmak ve tartismaktadir. Bayesian yaklasim, model seciminde kullanilan klasik P-degerlerine dayali likelihood-ratio testleri (LRT) ile karsilastirilmaktadir.
openaire   +3 more sources

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, Zixuan Zhang, Bingyan Li, Junkai Wang, Hongcheng Gu   +4 more
wiley   +1 more source

Recalibrating single-study effect sizes using hierarchical Bayesian models. [PDF]

Front Neuroimaging, 2023
Cao Z, McCabe M, Callas P, Cupertino RB, Ottino-González J, Murphy A, Pancholi D, Schwab N, Catherine O, Hutchison K, Cousijn J, Dagher A, Foxe JJ, Goudriaan AE, Hester R, Li CR, Thompson WK, Morales AM, London ED, Lorenzetti V, Luijten M, Martin-Santos R, Momenan R, Paulus MP, Schmaal L, Sinha R, Solowij N, Stein DJ, Stein EA, Uhlmann A, van Holst RJ, Veltman DJ, Wiers RW, Yücel M, Zhang S, Conrod P, Mackey S, Garavan H, ENIGMA Addiction Working Group.   +38 more
europepmc   +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

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

Comparing Bayesian Models of Annotation

Transactions of the Association for Computational Linguistics, 2021
Silviu Paun, Bob Carpenter, Jon Chamberlain, Dirk Hovy, Udo Kruschwitz, Massimo Poesio   +5 more
doaj   +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

Longitudinal hierarchical Bayesian models of covariate effects on airway and alveolar nitric oxide. [PDF]

Sci Rep, 2023
Weng J, Molshatzki N, Marjoram P, Gauderman WJ, Gilliland FD, Eckel SP.   +5 more
europepmc   +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

Leveraging Bayesian deep learning and ensemble methods for uncertainty quantification in image classification: A ranking-based approach

Heliyon
Bayesian deep learning (BDL) has emerged as a powerful technique for quantifying uncertainty in classification tasks, surpassing the effectiveness of traditional models by aligning with the probabilistic nature of real-world data.
Abdullah A. Abdullah, Masoud M. Hassan, Yaseen T. Mustafa   +2 more
doaj   +1 more source