Discrete choice modeling in the era of big data

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We study the statistical mechanics and the equilibrium dynamics of a system of classical Heisenberg spins with frustrated interactions on a d -dimensional simple hypercubic lattice, in the limit of infinite dimensionality d -> infinity . In the analysis we ...

Decision-making permeates every aspect of human and societal development, from individuals' daily choices to the complex decisions made by communities and institutions. Central to effective decision-making is the discipline of optimization, which seeks th ...

Human babies have a natural desire to interact with new toys and objects, through which they learn how the world around them works, e.g., that glass shatters when dropped, but a rubber ball does not. When their predictions are proven incorrect, such as whe ...

This document contains all the data and the details of the analysis used in the manuscript titled " Control of Ge island coalescence for the formation of nanowires on silicon." https://doi.org/10.1039/D3NH00573A ...

Image information about the state of a building after an earthquake, which can be collected without endangering the post-earthquake reconnaissance activities, can be used to reduce uncertainties in response predictions for future seismic events. This paper ...

Deep neural networks provide magnificent results for vision tasks. However, their complex structures and numerous parameters make them computationally and memory-wise intensive. Execution of these models on resource-constrained, camera-equipped devices suc ...

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Genome-wide chromatin conformation capture assays provide formidable insights into the spatial organization of genomes. However, due to the complexity of the data structure, their integration in multi-omics workflows remains challenging. We present data st ...

This data package supports the publication 'Complexity of crack front geometry enhances toughness of brittle solids' by Xinyue Wei, Chenzhuo Li, Cían McCarthy, and John M. Kolinski Nature physics (2024) - https://doi.org/10.1038/s41567-024-02435-x DOI: 1 ...

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 ...

Machine learning (ML) enables artificial intelligent (AI) agents to learn autonomously from data obtained from their environment to perform tasks. Modern ML systems have proven to be extremely effective, reaching or even exceeding human intelligence. Altho ...

The 70 kDa heat shock protein (Hsp70) chaperones control protein homeostasis in all ATP-containing cellular compartments. J-domain proteins (JDPs) coevolved with Hsp70s to trigger ATP hydrolysis and catalytically upload various substrate polypeptides in ne ...

Operators from various industries have been pushing the adoption of wireless sensing nodes for industrial monitoring, and such efforts have produced sizeable condition monitoring datasets that can be used to build diagnosis algorithms capable of warning ma ...

Discrete choice modeling in the era of big data

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Frustrated magnets in the limit of infinite dimensions: Dynamics and disorder-free glass transition

Reliable data-driven decision-making through optimal transport

Seeking the new, learning from the unexpected: Computational models of surprise and novelty in the brain

Data set for control of Ge island coalescence for the formation of nanowires on silicon

Reducing uncertainties in response predictions of earthquake-damaged masonry buildings using data from image-based inspection

Smart Edge for Hierarchical Vision Systems

Designing for Intimate Wellbeing: Aidee, a Qualitative Approach To Urine Home Monitoring

Resource-Efficient Continual Learning for Personalized Online Seizure Detection

Orchestrating chromosome conformation capture analysis with Bioconductor

Dataset for "Complexity of crack front geometry enhances toughness of brittle solids"

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

Few-shot Learning for Efficient and Effective Machine Learning Model Adaptation

Autorepression of yeast Hsp70 cochaperones by intramolecular interactions involving their J-domains

Federated learning with uncertainty-based client clustering for fleet-wide fault diagnosis