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D’ya Like DAGs? A Survey on Structure Learning and Causal Discovery

ACM computing surveys, 2022-11, Vol.55 (4), p.1-36, Article 82

2022

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Misspecification and Unreliable Interpretations in Psychology and Social Science

Psychological methods, 2023-06, Vol.28 (3), p.507-526

2023

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Emotion dynamic patterns between intimate relationship partners predict their separation two years later: A machine learning approach

PloS one, 2023-07, Vol.18 (7), p.e0288048-e0288048

2023

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Trying to outrun causality with machine learning: Limitations of model explainability techniques for exploratory research

Psychological methods, 2024-09

Vowels, Matthew J

2024

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Longitudinal evidence over 2 years of the pandemic shows that poor mental health in people living with obesity may be underestimated

PloS one, 2024-07, Vol.19 (7), p.e0305627

2024

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Using spectral and cross-spectral analysis to identify patterns and synchrony in couples' sexual desire

PloS one, 2018-10, Vol.13 (10), p.e0205330-e0205330

2018

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Spectral and Cross-Spectral Analysis-A Tutorial for Psychologists and Social Scientists

Psychological methods, 2023-06, Vol.28 (3), p.631-650

2023

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Uncovering the Most Important Factors for Predicting Sexual Desire Using Explainable Machine Learning

Journal of sexual medicine, 2021-07, Vol.18 (7), p.1198-1216

2021

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Typical Yet Unlikely and Normally Abnormal: The Intuition Behind High-Dimensional Statistics

Statistics, politics, and policy, 2024-03, Vol.15 (1), p.87-113

Vowels, Matthew J.

2024

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Is Infidelity Predictable? Using Explainable Machine Learning to Identify the Most Important Predictors of Infidelity

The Journal of sex research, 2022-02, Vol.59 (2), p.224-237

2022

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Identifying the strongest self-report predictors of sexual satisfaction using machine learning

Journal of social and personal relationships, 2022-05, Vol.39 (5), p.1191-1212

2022

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Prespecification of Structure for the Optimization of Data Collection and Analysis

Collabra. Psychology, 2023-02, Vol.9 (1)

2023

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Toward a causal link between attachment styles and mental health during the COVID‐19 pandemic

British journal of clinical psychology, 2023-09, Vol.62 (3), p.605-620

2023

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A Machine Learning Approach to Predicting Perceived Partner Support From Relational and Individual Variables

Social psychological & personality science, 2023-07, Vol.14 (5), p.526-538

2023

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What Can Be Learned From Couple Research: Examining Emotional Co-Regulation Processes in Face-to-Face Interactions

Journal of counseling psychology, 2020-07, Vol.67 (4), p.475-487

2020

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NestedVAE: Isolating Common Factors via Weak Supervision

2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020, p.9199-9209

2020

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Associations between daily positive communication and sexual desire and satisfaction: an approach utilizing traditional analyses and machine learning

Sexual and relationship therapy, 2023-09, p.1-26

2023

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Improving Robot Localisation by Ignoring Visual Distraction

2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021, p.3549-3554

2021

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VDSM: Unsupervised Video Disentanglement with State-Space Modeling and Deep Mixtures of Experts

2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021, p.8172-8182

2021

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Couple Perceptions as Mediators Between Family Economic Strain and Marital Quality: Evidence From Longitudinal Dyadic Data

Financial counseling and planning, 2021-01, Vol.32 (1), p.158-172

2021

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The Impact of Family Economic Strain On Work-Family Conflict, Marital Support, Marital Quality, and Marital Stability During the Middle Years

Journal of personal finance, 2019-01, Vol.18 (2), p.9-24

2019

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BERT meets LIWC: Exploring State-of-the-Art Language Models for Predicting Communication Behavior in Couples’ Conflict Interactions

Companion Publication of the 2021 International Conference on Multimodal Interaction, 2021, p.385-389

2021

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Shadow-Mapping for Unsupervised Neural Causal Discovery

2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2021, p.1740-1743

2021

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Targeted VAE: Variational and Targeted Learning for Causal Inference

2021 IEEE International Conference on Smart Data Services (SMDS), 2021, p.132-141

2021

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Gated Variational AutoEncoders: Incorporating Weak Supervision to Encourage Disentanglement

2020 15th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2020), 2020, p.125-132

2020

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D’ya Like DAGs? A Survey on Structure Learning and Causal Discovery

Misspecification and Unreliable Interpretations in Psychology and Social Science

Emotion dynamic patterns between intimate relationship partners predict their separation two years later: A machine learning approach

Trying to outrun causality with machine learning: Limitations of model explainability techniques for exploratory research

Longitudinal evidence over 2 years of the pandemic shows that poor mental health in people living with obesity may be underestimated

Using spectral and cross-spectral analysis to identify patterns and synchrony in couples' sexual desire

Spectral and Cross-Spectral Analysis-A Tutorial for Psychologists and Social Scientists

Uncovering the Most Important Factors for Predicting Sexual Desire Using Explainable Machine Learning

Typical Yet Unlikely and Normally Abnormal: The Intuition Behind High-Dimensional Statistics

Is Infidelity Predictable? Using Explainable Machine Learning to Identify the Most Important Predictors of Infidelity

Identifying the strongest self-report predictors of sexual satisfaction using machine learning

Prespecification of Structure for the Optimization of Data Collection and Analysis

Toward a causal link between attachment styles and mental health during the COVID‐19 pandemic

A Machine Learning Approach to Predicting Perceived Partner Support From Relational and Individual Variables

What Can Be Learned From Couple Research: Examining Emotional Co-Regulation Processes in Face-to-Face Interactions

NestedVAE: Isolating Common Factors via Weak Supervision

Associations between daily positive communication and sexual desire and satisfaction: an approach utilizing traditional analyses and machine learning

Improving Robot Localisation by Ignoring Visual Distraction

VDSM: Unsupervised Video Disentanglement with State-Space Modeling and Deep Mixtures of Experts

Couple Perceptions as Mediators Between Family Economic Strain and Marital Quality: Evidence From Longitudinal Dyadic Data

The Impact of Family Economic Strain On Work-Family Conflict, Marital Support, Marital Quality, and Marital Stability During the Middle Years

BERT meets LIWC: Exploring State-of-the-Art Language Models for Predicting Communication Behavior in Couples’ Conflict Interactions

Shadow-Mapping for Unsupervised Neural Causal Discovery

Targeted VAE: Variational and Targeted Learning for Causal Inference

Gated Variational AutoEncoders: Incorporating Weak Supervision to Encourage Disentanglement

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