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A comprehensive workflow for general-purpose neural modeling with highly configurable neuromorphic hardware systems

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We propose a method for adapting neural networks to distribution shifts at test-time. In contrast to training-time robustness mechanisms that attempt to anticipate and counter the shift, we create a closed-loop system and make use of test-time feedback sig ...

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Modeling and simulation of neocortical micro- and mesocircuitry. Part II: Physiology and experimentation

Henry Markram, Felix Schürmann, James Gonzalo King, Rajnish Ranjan, Srikanth Ramaswamy, Alexis Arnaudon, Eilif Benjamin Muller, Daniel Keller, Michael Reimann, Vishal Sood, Jean-Denis Georges Emile Courcol, Werner Alfons Hilda Van Geit, Giuseppe Chindemi, Michael Emiel Gevaert, Pramod Shivaji Kumbhar, Armando Romani, Christian Andreas Rössert, Judit Planas Carbonell, Genrich Ivaska, András Ecker, Daniela Egas Santander, Natali Barros Zulaica, Alexander Dietz, Omar Awile, Samuel Lieven D. Lapere, Matthias Wolf, Sirio Bolaños Puchet, Thomas Brice Delemontex, Jorge Blanco Alonso, Mustafa Anil Tuncel, Tanguy Pierre Louis Damart, Maria Reva, James Bryden Isbister, Darshan Mandge, Weina Ji, Aleksandra Zuzanna Teska, Polina Litvak, Gianluca Ficarelli, Joni Henrikki Herttuainen, Christoph Pokorny, Elvis Boci

Cortical dynamics underlie many cognitive processes and emerge from complex multi-scale interactions, which are challenging to study in vivo. Large-scale, biophysically detailed models offer a tool which can complement laboratory approaches. We present a m ...

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Post-Moore's Law Fusion: High-Bandwidth Memory, Accelerators, and Native Half-Precision Processing for CPU-Local Analytics

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Modern data management systems aim to provide both cutting-edge functionality and hardware efficiency. With the advent of AI-driven data processing and the post-Moore Law era, traditional memory-bound scale-up data management operations face scalability ch ...

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Deep Learning for 3D Surface Modelling and Reconstruction

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In recent years, there has been a significant revolution in the field of deep learning, which has demonstrated its effectiveness in automatically capturing intricate patterns from large datasets. However, the majority of these successes in Computer Vision ...

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Hybrid perovskites have attracted enormous attention in the next generation resistive switching (RS) memristor for the artificial synapses, owing to their ambipolar charge transport, long diffusion length, and tunable visible bandgap. However, the variable ...

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Agent-based simulations have been widely applied in many disciplines, by scientists and engineers alike. Scientists use agent-based simulations to tackle global problems, including alleviating poverty, reducing violence, and predicting the impact of pandem ...

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IEEE2023