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Clinical characteristics of 80 subjects with KCNQ2-related encephalopathy: Results from a family-driven survey

Epilepsy & behavior, 2023-05, Vol.142, p.109153-109153, Article 109153

2023

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Deep neural networks rival the representation of primate IT cortex for core visual object recognition

PLoS computational biology, 2014-12, Vol.10 (12), p.e1003963

2014

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Deep Neural Networks as a Computational Model for Human Shape Sensitivity

PLoS computational biology, 2016-04, Vol.12 (4), p.e1004896-e1004896

2016

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Objective Criteria in the Medicinal Therapy for Type II Diabetes: An Analysis of the Patients' Perspective with Analytic Hierarchy Process and Best-Worst Scaling

Gesundheitswesen (Bundesverband der Ärzte des Öffentlichen Gesundheitsdienstes (Germany)), 2016-05, Vol.78 (5), p.326

2016

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Hye and me as Identical Currencies in Preference Studies? A Discrete-Choice Experiment in Type2 Diabetes Mellitus

Value in health, 2014-11, Vol.17 (7), p.A355-A355

2014

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Patients' Preferences in Oral Diabetes Treatment: A Discrete Choice Experiment in Type2 Diabetes Mellitus

Value in health, 2014-11, Vol.17 (7), p.A355-A355

2014

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Patients' Preferences in Late Stage Treatment of Non-Small-Cell Lung Cancer: A Discrete-Choice Experiment

Value in health, 2014-11, Vol.17 (7), p.A650-A650

2014

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Learning Universal Computations with Spikes

PLoS computational biology, 2016-06, Vol.12 (6), p.e1004895-e1004895

2016

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Inferring nonlinear neuronal computation based on physiologically plausible inputs

PLoS computational biology, 2013-07, Vol.9 (7), p.e1003143-e1003143

2013

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Endovenous treatment of the greater saphenous vein with a 940-nm diode laser: Thrombotic occlusion after endoluminal thermal damage by laser-generated steam bubbles

Journal of vascular surgery, 2002-04, Vol.35 (4), p.729-736

2002

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A state space approach for piecewise-linear recurrent neural networks for identifying computational dynamics from neural measurements

PLoS computational biology, 2017-06, Vol.13 (6), p.e1005542-e1005542

2017

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Characteristics of integrated care programmes and their impact on patient benefit: a discrete-choice experiment for integrated care networks

Gesundheitswesen (Bundesverband der Ärzte des Öffentlichen Gesundheitsdienstes (Germany)), 2015-05, Vol.77 (5), p.340

2015

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Using Matrix and Tensor Factorizations for the Single-Trial Analysis of Population Spike Trains

PLoS computational biology, 2016-11, Vol.12 (11), p.e1005189-e1005189

2016

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Patients Preferences Regarding the Treatment of Type II Diabetes Mellitus: Comparison of Best-Worst Scaling and Analytic Hierarchy Process

Value in health, 2013-11, Vol.16 (7), p.A446-A446

2013

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Patients Preferences for Long-Term Treatment After Acute Coronary Syndrome: A Discrete-Choice Experiment and Analytic Hierarchy Process

Value in health, 2013-11, Vol.16 (7), p.A534-A534

2013

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Model Constrained by Visual Hierarchy Improves Prediction of Neural Responses to Natural Scenes

PLoS computational biology, 2016-06, Vol.12 (6), p.e1004927-e1004927

2016

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Adaptive Spike Threshold Enables Robust and Temporally Precise Neuronal Encoding

PLoS computational biology, 2016-06, Vol.12 (6), p.e1004984-e1004984

2016

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Emerging Object Representations in the Visual System Predict Reaction Times for Categorization

PLoS computational biology, 2015-06, Vol.11 (6), p.e1004316-e1004316

2015

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High Accuracy Decoding of Dynamical Motion from a Large Retinal Population

PLoS computational biology, 2015-07, Vol.11 (7), p.e1004304-e1004304

2015

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Efficient "Shotgun" Inference of Neural Connectivity from Highly Sub-sampled Activity Data

PLoS computational biology, 2015-10, Vol.11 (10), p.e1004464-e1004464

2015

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Visual nonclassical receptive field effects emerge from sparse coding in a dynamical system

PLoS computational biology, 2013-08, Vol.9 (8), p.e1003191-e1003191

2013

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Where's the Noise? Key Features of Spontaneous Activity and Neural Variability Arise through Learning in a Deterministic Network

PLoS computational biology, 2015-12, Vol.11 (12), p.e1004640-e1004640

2015

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PIH36 A Discrete Choice Experiment in Different Health States: Patient Preferences for Patient-Centered Health Care Delivery Systems

Value in health, 2012-06, Vol.15 (4), p.A198-A198

2012

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Approximate Inference for Time-Varying Interactions and Macroscopic Dynamics of Neural Populations

PLoS computational biology, 2017-01, Vol.13 (1), p.e1005309-e1005309

2017

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Measuring Fisher information accurately in correlated neural populations

PLoS computational biology, 2015-06, Vol.11 (6), p.e1004218-e1004218

2015

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Clinical characteristics of 80 subjects with KCNQ2-related encephalopathy: Results from a family-driven survey

Deep neural networks rival the representation of primate IT cortex for core visual object recognition

Deep Neural Networks as a Computational Model for Human Shape Sensitivity

Objective Criteria in the Medicinal Therapy for Type II Diabetes: An Analysis of the Patients' Perspective with Analytic Hierarchy Process and Best-Worst Scaling

Hye and me as Identical Currencies in Preference Studies? A Discrete-Choice Experiment in Type2 Diabetes Mellitus

Patients' Preferences in Oral Diabetes Treatment: A Discrete Choice Experiment in Type2 Diabetes Mellitus

Patients' Preferences in Late Stage Treatment of Non-Small-Cell Lung Cancer: A Discrete-Choice Experiment

Learning Universal Computations with Spikes

Inferring nonlinear neuronal computation based on physiologically plausible inputs

Endovenous treatment of the greater saphenous vein with a 940-nm diode laser: Thrombotic occlusion after endoluminal thermal damage by laser-generated steam bubbles

A state space approach for piecewise-linear recurrent neural networks for identifying computational dynamics from neural measurements

Characteristics of integrated care programmes and their impact on patient benefit: a discrete-choice experiment for integrated care networks

Using Matrix and Tensor Factorizations for the Single-Trial Analysis of Population Spike Trains

Patients Preferences Regarding the Treatment of Type II Diabetes Mellitus: Comparison of Best-Worst Scaling and Analytic Hierarchy Process

Patients Preferences for Long-Term Treatment After Acute Coronary Syndrome: A Discrete-Choice Experiment and Analytic Hierarchy Process

Model Constrained by Visual Hierarchy Improves Prediction of Neural Responses to Natural Scenes

Adaptive Spike Threshold Enables Robust and Temporally Precise Neuronal Encoding

Emerging Object Representations in the Visual System Predict Reaction Times for Categorization

High Accuracy Decoding of Dynamical Motion from a Large Retinal Population

Efficient "Shotgun" Inference of Neural Connectivity from Highly Sub-sampled Activity Data

Visual nonclassical receptive field effects emerge from sparse coding in a dynamical system

Where's the Noise? Key Features of Spontaneous Activity and Neural Variability Arise through Learning in a Deterministic Network

PIH36 A Discrete Choice Experiment in Different Health States: Patient Preferences for Patient-Centered Health Care Delivery Systems

Approximate Inference for Time-Varying Interactions and Macroscopic Dynamics of Neural Populations

Measuring Fisher information accurately in correlated neural populations

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