Results 71 to 80 of about 155,766 (268)
Penerapan Algortima Tree Augmented Naive Bayesian pada Penentuan Peubah Penting
, 2011 Peningkatan kinerja produk sangat penting di era persaingan pasar bebas. Salah satu cara untuk mengoptimalkan peningkatan kinerja suatu produk, produsen harus mengetahui tingkat kepentingan peubah dari produknya.
Awalia, Pingkan
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The design of a Bayesian Network for mobility management in Wireless Sensor Networks [PDF]
, 2010 Mobility in Wireless Sensor Networks (WSNs) is achieved by attaching sensors to mobile objects such as animals (Juang et al. 2002), people (Campbell et al. 2008), and robots (Dantu et al. 2005).
Wachowicz, Monica +3 more
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Dynamic Bayesian networks in molecular plant science: inferring gene regulatory networks from multiple gene expression time series [PDF]
, 2011 To understand the processes of growth and biomass production in plants, we ultimately need to elucidate the structure of the underlying regulatory networks at the molecular level.
Dondelinger, F. +8 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
Modeling technology based on fuzzy object-oriented Bayesian belief networks
, 2018 The basic components of information technology inductive modeling causation under uncertainty based on fuzzy object-oriented Bayesian networks is proposed.
Kostukevich, F.V., Yershov, S.V.
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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 Approach to Network Modularity
Physical Review Letters, 2008 We present an efficient, principled, and interpretable technique for inferring module assignments and for identifying the optimal number of modules in a given network. We show how several existing methods for finding modules can be described as variant, special, or limiting cases of our work, and how the method overcomes the resolution limit problem ...
Hofman, Jake M., Wiggins, Chris H.
openaire +4 more sources
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
Transformers are Bayesian Networks
CoRRTransformers are the dominant architecture in AI, yet why they work remains poorly understood. This paper offers a precise answer: a transformer is a Bayesian network. We establish this in five ways. First, we prove that every sigmoid transformer with any weights implements weighted loopy belief propagation on its implicit factor graph.
openaire +2 more sources
Bayesian networks in environmental modelling
Environmental Modelling & Software, 2011 Bayesian networks (BNs), also known as Bayesian belief networks or Bayes nets, are a kind of probabilistic graphical model that has become very popular to practitioners mainly due to the powerful probability theory involved, which makes them able to deal with a wide range of problems.The goal of this review is to show how BNs are being used in ...
Pedro Aguilera Aguilera +4 more
openaire +2 more sources