Concept

Physical neural network

Related publications (295)

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This article summarizes the recent advancements in the design, fabrication, and control of microrobotic devices for the diagnosis and treatment of brain disorders. With a focus on diverse actuation methods, we discuss how advancements in materials science ...

2024

Mitigating Object Dependencies: Improving Point Cloud Self-Supervised Learning through Object Exchange

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In the realm of point cloud scene understanding, particularly in indoor scenes, objects are arranged following human habits, resulting in objects of certain semantics being closely positioned and displaying notable inter-object correlations. This can creat ...

2024

InterpretCC: Intrinsic User-Centric Interpretability through Global Mixture of Experts

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Interpretability for neural networks is a trade-off between three key requirements: 1) faithfulness of the explanation (i.e., how perfectly it explains the prediction), 2) understandability of the explanation by humans, and 3) model performance. Most exist ...

2024

Deep Learning Theory Through the Lens of Diagonal Linear Networks

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

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EPFL2024

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

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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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Emulating Multimemristive Behavior of Silicon Nanowire-Based Biosensors by Using CMOS-Based Implementations

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The research presented in this article draws inspiration from previous efforts aimed at replicating the functions of various solid-state memristors using a variety of materials. The memristor circuit emulator serves as a cost-effective tool for circuit des ...

Ieee-Inst Electrical Electronics Engineers Inc2024

Whole-heart electromechanical simulations using Latent Neural Ordinary Differential Equations

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Cardiac digital twins provide a physics and physiology informed framework to deliver personalized medicine. However, high-fidelity multi-scale cardiac models remain a barrier to adoption due to their extensive computational costs. Artificial Intelligence-b ...

Nature Portfolio2024

Task-driven neural network models predict neural dynamics of proprioception: Experimental data, activations and predictions of neural network models

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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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Memristive Control of Plasmon-Mediated Nonlinear Photoluminescence in Au Nanowires

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Nonlinear photoluminescence (N-PL) is a broadband photon emission arising from a nonequilibrium heated electron distribution generated at the surface of metallic nanostructures by ultrafast pulsed laser illumination. N-PL is sensitive to surface morphology ...

Amer Chemical Soc2024

3D trigonal FAPbI(3)-based multilevel resistive switching nonvolatile memory for artificial neural synapse

Mohammad Khaja Nazeeruddin, Paul Joseph Dyson, Yong Ding, Li Tao, Yao Zhang, Jun Zhang, Bowen Jiang

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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Deep Learning Theory Through the Lens of Diagonal Linear Networks

Scott William Pesme

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

2

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

EPFL2024