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Fast Thermal Simulation of 2D/3D Integrated Circuits Exploiting Neural Networks and GPUs

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Magnonics is a research field that has gained an increasing interest in both the fundamental and applied sciences in recent years. This field aims to explore and functionalize collective spin excitations in magnetically ordered materials for modern informa ...

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Thermal conductivity of Li 3 PS 4 solid electrolytes with ab initio accuracy

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The vast amount of computational studies on electrical conduction in solid-state electrolytes is not mirrored by comparable efforts addressing thermal conduction, which has been scarcely investigated despite its relevance to thermal management and (over)he ...

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Nuclear power is a powerful technology that plays an important role in the fight against climate change, and research is continuously engaged in studies that could further improve its safety. After the Fukushima accident, Accident Tolerant Fuels research h ...

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In this paper, we consider experimental data available for graphene-based nanolubricants to evaluate their convective heat transfer performance by means of computational fluid dynamics (CFD) simulations. Single-phase models with temperature-dependent prope ...

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Modern integrated circuits are tiny yet incredibly complex technological artifacts, composed of millions and billions of individual structures working in unison. Managing their complexity and facilitating their design drove part of the co-evolution of mode ...

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General and Unified Model of the Power Flow Problem in Multiterminal AC/DC Networks

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The time-honored Allen -Feldman theory of heat transport in glasses is generally assumed to predict a finite value for the thermal conductivity, even if it neglects the anharmonic broadening of vibrational normal modes. We demonstrate that the harmonic app ...

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Here we provide the neural data, activation and predictions for the best models and result dataframes of our article "Task-driven neural network models predict neural dynamics of proprioception". It contains the behavioral and neural experimental data (cu ...

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Advanced Silicon and SWIR Single-Photon Avalanche Diodes: Design, Simulation, and Characterization

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The ability to reason, plan and solve highly abstract problems is a hallmark of human intelligence. Recent advancements in artificial intelligence, propelled by deep neural networks, have revolutionized disciplines like computer vision and natural language ...

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Task-driven neural network models predict neural dynamics of proprioception: Neural network model weights

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Proprioception tells the brain the state of the body based on distributed sensors in the body. However, the principles that govern proprioceptive processing from those distributed sensors are poorly understood. Here, we employ a task-driven neural network ...

Zenodo2024

Gibbs sampling the posterior of neural networks

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In this paper, we study sampling from a posterior derived from a neural network. We propose a new probabilistic model consisting of adding noise at every pre- and post-activation in the network, arguing that the resulting posterior can be sampled using an ...

Iop Publishing Ltd2024