Interplay Between Topology and Social Learning Over Weak Graphs

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Research in artificial intelligence (AI) and neural network (NN) technologies has been boosted by recent hardware advances, while the emergence of self-synthesized materials such as nanocarbons has attracted much attention to overcome the limitations of Si ...

This special issue explores the burgeoning field of deep learning for remote sensing time series analysis. The 20 contributed papers showcase diverse applications, including land cover mapping, change detection, atmospheric and biophysical/biochemical para ...

The present work proposes a framework for nonlinear model order reduction based on a Graph Convolutional Autoencoder (GCA-ROM). In the reduced order modeling (ROM) context, one is interested in obtaining real -time and many-query evaluations of parametric ...

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Understanding how convolutional neural networks (CNNs) can efficiently learn high-dimensional functions remains a fundamental challenge. A popular belief is that these models harness the local and hierarchical structure of natural data such as images. Yet, ...

The rapid progress in machine learning in recent years has been based on a highly productive connection to gradient-based optimization. Further progress hinges in part on a shift in focus from pattern recognition to decision-making and multi-agent problems ...

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We investigate the problem of fluid injection at constant pressure in a 2D Discrete Fracture Network (DFN) with randomly oriented and uniformly distributed frictionally-stable fractures. We show that this problem shares similarities with the simpler scenar ...

This paper establishes the close relation that exists between the Fano noise suppression factor F and the Gm/ID FoM showing that F is proportional to the product of the thermal noise excess factor γn and the normalized Gm/ID function. Taking advantage of t ...

Time series analysis has proven to be a powerful method to characterize several phenomena in biology, neuroscience and economics, and to understand some of their underlying dynamical features. Several methods have been proposed for the analysis of multivar ...

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Since polar were ratified as part of the 5G standard, low-complexity polar decoders with close-to-optimum error-rate performance have received significant attention. Compared to successive cancellation (SC) decoding, both SC list and SC flip decoding can i ...

Cemented granular materials are abundant in nature and are often artificially produced. Their macroscopic behaviour is driven by small-scale material processes, which are generally classified as: grain breakage, cement damage and fragment rearrangement. Th ...

The use of molecular dynamics (MD) simulations has led to promising results to unravel the atomistic origins of adhesive wear, and in particular for the onset of wear at nanoscale surface asperities. However, MD simulations come with a high computational c ...

Animal behavior emerges from an interaction between neural network dynamics, musculoskeletal properties and the physical environment. Accessing and understanding the interplay between these elements requires the development of integrative and morphological ...

Interplay Between Topology and Social Learning Over Weak Graphs

Chat with Graph Search

Split weight distribution learning for binary neural networks exploiting nano-memristive graphene/sumanene/graphene devices

Preface: Advancing deep learning for remote sensing time series data analysis

A graph convolutional autoencoder approach to model order reduction for parametrized PDEs

Collective relational inference for learning heterogeneous interactions

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A gentle introduction to gradient-based optimization and variational inequalities for machine learning

Fast and robust parameter estimation with uncertainty quantification for the cardiac function

Injection-Induced Aseismic Slip in Tight Fractured Rocks

The Fano Noise Suppression Factor and the Gm/ID FoM

Higher-order organization of multivariate time series

Polynomial-time universality and limitations of deep learning

Engineered substrates incapable of induction of chondrogenic differentiation compared to the chondrocyte imprinted substrates

Training Efficient Controllers via Analytic Policy Gradient

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Dynamic SCL Decoder With Path-Flipping for 5G Polar Codes

Micromechanically inspired investigation of cemented granular materials: part I-from X-ray micro tomography to measurable model variables

Adhesive wear with a coarse-grained discrete element model

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