Soft Printable Electrode Coating for Neural Interfaces

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The conception of epoxy thermosets with both reprocessability and flame retardancy delineates a new horizon in polymer science, offering a material solution that is not only superior in fire safety but is also environment friendly. Herein, a flame-retardan ...

The capabilities of deep learning systems have advanced much faster than our ability to understand them. Whilst the gains from deep neural networks (DNNs) are significant, they are accompanied by a growing risk and gravity of a bad outcome. This is troubli ...

The performance of machine learning algorithms is conditioned by the availability of training datasets, which is especially true for the field of nondestructive evaluation. Here we propose one reconfigurable specimen instead of numerous reference specimens ...

Integrating smart algorithms on neural devices presents significant opportunities for various brain disorders. In this paper, we review the latest advancements in the development of three categories of intelligent neural prostheses featuring embedded signa ...

Photometric stereo, a computer vision technique for estimating the 3D shape of objects through images captured under varying illumination conditions, has been a topic of research for nearly four decades. In its general formulation, photometric stereo is an ...

Designing novel materials is greatly dependent on understanding the design principles, physical mechanisms, and modeling methods of material microstructures, requiring experienced designers with expertise and several rounds of trial and error. Although rec ...

Subcortical brain structures such as the basal ganglia or the thalamus are involved in regulating motor and cognitive behavior. However, their contribution to perceptual consciousness is still unclear, due to the inherent difficulties of recording subcorti ...

The upcoming Square Kilometre Array Observatory will produce images of neutral hydrogen distribution during the epoch of reionization by observing the corresponding 21-cm signal. However, the 21-cm signal will be subject to instrumental limitations such as ...

Turning pass-through network architectures into iterative ones, which use their own output as input, is a well-known approach for boosting performance. In this paper, we argue that such architectures offer an additional benefit: The convergence rate of the ...

In this PhD manuscript, we explore optimisation phenomena which occur in complex neural networks through the lens of

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-layer diagonal linear networks. This rudimentary architecture, which consists of a two layer feedforward linear network with a diagonal ...

Soft Printable Electrode Coating for Neural Interfaces

Chat with Graph Search

Enabling simultaneous reprocessability and fire protection via incorporation of phosphine oxide monomer in epoxy vitrimer

Safe Deep Neural Networks

Reduced Training Data for Laser Ultrasound Signal Interpretation by Neural Networks

Intelligent Neural Interfaces: An Emerging Era in Neurotechnology

Aggregating Spatial and Photometric Context for Photometric Stereo

Text-to-Microstructure Generation Using Generative Deep Learning

Subcortical correlates of consciousness with human single neuron recordings

Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination

Enabling Uncertainty Estimation in Iterative Neural Networks

Deep Learning Theory Through the Lens of Diagonal Linear Networks