Results 131 to 140 of about 238,312 (311)
, 2023 Auxetics are a rare class of materials that exhibit a negative Poisson\u27s ratio. The existence of these auxetic materials is rare but has a large number of applications in designing exotic materials.
Raheel, Hammad, Sownyak , Mondal
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Temporal Interference Stimulation Enhances Neural Regeneration
Advanced Science, EarlyView.Temporal interference (TI) stimulation is proposed as a non‐invasive approach to enhance neural regeneration in the deep brain. Theta‐band TI modulation selectively promotes neural progenitor cell differentiation in vitro and augments hippocampal neurogenesis in amouse model of Alzheimer's disease‐like amyloidosis.
Sofia Peressotti +15 more
wiley +1 more source
Negative sampling in semi-supervised learning
CoRR, 2019 We introduce Negative Sampling in Semi-Supervised Learning (NS3L), a simple, fast, easy to tune algorithm for semi-supervised learning (SSL). NS3L is motivated by the success of negative sampling/contrastive estimation. We demonstrate that adding the NS3L loss to state-of-the-art SSL algorithms, such as the Virtual Adversarial Training (VAT ...
John Chen 0002 +2 more
openaire +3 more sources
Semi-Supervised Neural Gas for Adaptive Brain-Computer Interfaces
, 2012 Riechmann H, Finke A. Semi-Supervised Neural Gas for Adaptive Brain-Computer Interfaces. In: ESANN 2012 proceedings. i6doc.com; 2012: 121-126.Non-stationarity is inherent in EEG data.
Riechmann, Hannes +1 more
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Advanced Science, EarlyView.Short‐range order in 2D transition metal dichalcogenides is revealed as a new design paradigm. Driven by chemical affinity and atomic size, it governs properties across scales. Weak ordering tunes site‐resolved magnetism and d‐band centers, while strong ordering eliminates gap states to open band gaps.
Hanyu Liu +3 more
wiley +1 more source
Semi-Supervised Learning with Ladder Networks
CoRR, 2015 We combine supervised learning with unsupervised learning in deep neural networks. The proposed model is trained to simultaneously minimize the sum of supervised and unsupervised cost functions by backpropagation, avoiding the need for layer-wise pre-training.
Antti Rasmus +4 more
openaire +3 more sources
Convex Multiview Semi-Supervised Classification
, 2017 In many practical applications, there are a great number of unlabeled samples available, while labeling them is a costly and tedious process. Therefore, how to utilize unlabeled samples to assist digging out potential information about the problem is ...
Feiping Nie +5 more
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Advanced Science, EarlyView.This study presents an anatomical landmark‐guided DRL framework for autonomous wireless capsule endoscopy navigation. Using a lightweight edge‐contour‐depth fusion module, it achieves over 97% coverage across diverse gastric anatomies. To ensure reliability, a two‐stage sim‐to‐real pipeline with an adaptive dynamic programming controller mitigates ...
Haoxuan Wu +16 more
wiley +1 more source
CBARS: cluster based classification for activity recognition systems [PDF]
, 2012 Activity recognition focuses on inferring current user activities by leveraging sensory data available on today’s sensor rich environment. Supervised learning has been applied pervasively for activity recognition.
Gaber, Mohamed Medhat +11 more
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Advanced Science, EarlyView.A conversion‐resolved constitutive framework is developed for the hydrogen‐based direct reduction of iron oxide pellets. Effective reaction and transport timescales are inferred directly from measured trajectories and mapped against operating conditions, pellet architecture, and composition. The analysis reveals how late‐stage transport control emerges
Anurag Bajpai +3 more
wiley +1 more source