Blinking long-range connections increase the functionality of locally connected networks

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

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 ...

A modular multiple frequency coils inductive link system to wirelessly provide power for at least a medical implant at an output of a receiving coil, whereby the receiving coil is configured to be implanted in an organism. The modular multiple frequency co ...

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 ...

Nonlinear epsilon-near-zero (ENZ) nanodevices featuring vanishing permittivity and CMOS-compatibility are attractive solutions for large-scale-integrated systems-on-chips. Such confined systems with unavoidable heat generation impose critical challenges fo ...

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 ...

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 ...

Despite the widespread empirical success of ResNet, the generalization properties of deep ResNet are rarely explored beyond the lazy training regime. In this work, we investigate scaled ResNet in the limit of infinitely deep and wide neural networks, of wh ...

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 ...

In the rapidly evolving landscape of machine learning research, neural networks stand out with their ever-expanding number of parameters and reliance on increasingly large datasets. The financial cost and computational resources required for the training p ...

Deep learning has revolutionized the field of computer vision, a success largely attributable to the growing size of models, datasets, and computational power. Simultaneously, a critical pain point arises as several computer vision applications are deploye ...

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 ...

Recently, cutting-edge brain-machine interfaces (BMIs) have revealed the potential of decoders such as recurrent neural networks (RNNs) in predicting attempted handwriting [1] or speech [2], enabling rapid communication recovery after paralysis. However, c ...

Throughout history, the pace of knowledge and information sharing has evolved into an unthinkable speed and media. At the end of the XVII century, in Europe, the ideas that would shape the "Age of Enlightenment" were slowly being developed in coffeehouses, ...

The field of biometrics, and especially face recognition, has seen a wide-spread adoption the last few years, from access control on personal devices such as phones and laptops, to automated border controls such as in airports. The stakes are increasingly ...

The optical domain presents potential avenues for enhancing both computing and communication due to its inherent properties of bandwidth, parallelism, and energy efficiency. This research focuses on harnessing 3-Dimensional (3D) diffractive optics for nove ...

Next-generation implantable computational devices require long-term-stable electronic components capable of operating in, and interacting with, electrolytic surroundings without being damaged. Organic electrochemical transistors (OECTs) emerged as fitting ...

Over the last decades, implantable neural interfaces have been extensively explored and effectively deployed to address neurological and mental health disorders. The existing solutions present several limitations. Firstly, the physical size of the implanta ...

The miniaturization of integrated circuits (ICs) and their higher performance and energy efficiency, combined with new machine learning algorithms and applications, have paved the way to intelligent, interconnected edge devices. In the medical domain, they ...

The integration of technology in the medical field has greatly improved accuracy in diagnoses, thus leading to more effective treatments. Wearable and implantable medical devices offer great potential for remote patient monitoring, particularly for heart f ...

This thesis focuses on two selected learning problems: 1) statistical inference on graphs models, and, 2) gradient descent on neural networks, with the common objective of defining and analysing the measures that characterize the fundamental limits. In th ...

Blinking long-range connections increase the functionality of locally connected networks

Chat with Graph Search

The 2024 Magnonics Roadmap

A modular multiple frequency inductive link to wirelessly power multiple miniaturized implants

Graph generative deep learning models with an application to circuit topologies

Thermo-optic epsilon-near-zero effects

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

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

Generalization of Scaled Deep ResNets in the Mean-Field Regime

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

Random matrix methods for high-dimensional machine learning models

Fast and Future: Towards Efficient Forecasting in Video Semantic Segmentation

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

33.3 MiBMI: A 192/512-Channel 2.46mm² Miniaturized Brain-Machine Interface Chipset Enabling 31-Class Brain-to-Text Conversion Through Distinctive Neural Codes

Machine Learning for Modeling Stock Returns

Performing and Detecting Backdoor Attacks on Face Recognition Algorithms

3D diffractive optics for linear interconnects and nonlinear processing

In Liquido Computation with Electrochemical Transistors and Mixed Conductors for Intelligent Bioelectronics

Miniaturised, Wireless and Distributed Neural Interface Toward Cortical Visual Prosthesis

Exploring brain-inspired multi-core heterogeneous hardware templates for low-power biomedical embedded systems

Integrated Electronics for Deep Implants to Remotely Monitor Hemodynamics

Fundamental Limits in Statistical Learning Problems: Block Models and Neural Networks