Publications associées à Linear probability model

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

Alexander Mathis, Alberto Silvio Chiappa, Alessandro Marin Vargas, Axel Bisi

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 ...

EPFL Infoscience2024

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Linear probability model

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

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Chattez avec Graph Search

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

Comparing transferability in neural network approaches and linear models for machine-learning interaction potentials

Evaluating contrast sensitivity in early and intermediate age-related Macular Degeneration with the Quick Contrast Sensitivity Function

The inductive bias of deep learning: Connecting weights and functions

Inter-Individual Variability in Motor Output Is Driven by Recruitment Gain in the Corticospinal Tract Rather Than Motor Threshold

Local Kernel Regression and Neural Network Approaches to the Conformational Landscapes of Oligopeptides

Data-Driven Predictive Models: Calculational Bias in Characterization of Spent Nuclear Fuel

Multivariate time series forecasting for freeway networks

Inflight Microwave Drying Process of Micro-droplets for High Resolution 3D printing

Mesoscopic modeling of hidden spiking neurons

Evaluating contrast sensitivity in early and intermediate age-related Macular Degeneration with the Quick Contrast Sensitivity Function

Multivariate time series forecasting for freeway networks

Data-Driven Predictive Models: Calculational Bias in Characterization of Spent Nuclear Fuel

The inductive bias of deep learning: Connecting weights and functions

Inflight Microwave Drying Process of Micro-droplets for High Resolution 3D printing

Mesoscopic modeling of hidden spiking neurons

Local Kernel Regression and Neural Network Approaches to the Conformational Landscapes of Oligopeptides

Comparing transferability in neural network approaches and linear models for machine-learning interaction potentials

Inter-Individual Variability in Motor Output Is Driven by Recruitment Gain in the Corticospinal Tract Rather Than Motor Threshold