Matthew J. Vowels

According to our database, Matthew J. Vowels authored at least 18 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Deepfake Detection in Super-Recognizers and Police Officers.

Meike Ramon, Matthew J. Vowels, Matthew Groh

IEEE Secur. Priv., 2024

CaTs and DAGs: Integrating Directed Acyclic Graphs with Transformers and Fully-Connected Neural Networks for Causally Constrained Predictions.

Matthew J. Vowels, Mathieu Rochat, Sina Akbari

CoRR, 2024

psifx - Psychological and Social Interactions Feature Extraction Package.

Guillaume Rochette, Matthew J. Vowels

CoRR, 2024

2023

A Free Lunch with Influence Functions? An Empirical Evaluation of Influence Functions for Average Treatment Effect Estimation.

Matthew James Vowels, Sina Akbari, Necati Cihan Camgöz, Richard Bowden

Trans. Mach. Learn. Res., 2023

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

Matthew J. Vowels, Necati Cihan Camgöz, Richard Bowden

ACM Comput. Surv., 2023

SLEM: Machine Learning for Path Modeling and Causal Inference with Super Learner Equation Modeling.

Matthew J. Vowels

CoRR, 2023

Causal Effect Identification in Uncertain Causal Networks.

Sina Akbari, Fateme Jamshidi, Ehsan Mokhtarian, Matthew J. Vowels, Jalal Etesami, Negar Kiyavash

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Causal Discovery in Probabilistic Networks with an Identifiable Causal Effect.

Sina Akbari, Fateme Jamshidi, Ehsan Mokhtarian, Matthew J. Vowels, Jalal Etesami, Negar Kiyavash

CoRR, 2022

Trying to Outrun Causality with Machine Learning: Limitations of Model Explainability Techniques for Identifying Predictive Variables.

Matthew J. Vowels

CoRR, 2022

A Free Lunch with Influence Functions? Improving Neural Network Estimates with Concepts from Semiparametric Statistics.

Matthew J. Vowels, Sina Akbari, Jalal Etesami, Necati Cihan Camgöz, Richard Bowden

CoRR, 2022

2021

Targeted VAE: Variational and Targeted Learning for Causal Inference.

Matthew J. Vowels, Necati Cihan Camgöz, Richard Bowden

Proceedings of the IEEE International Conference on Smart Data Services, 2021

Improving Robot Localisation by Ignoring Visual Distraction.

Oscar Mendez Maldonado, Matthew J. Vowels, Richard Bowden

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021

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

Jacopo Biggiogera, George Boateng, Peter Hilpert, Matthew J. Vowels, Guy Bodenmann, Mona Neysari, Fridtjof Nussbeck, Tobias Kowatsch

Proceedings of the ICMI '21 Companion: Companion Publication of the 2021 International Conference on Multimodal Interaction, Montreal, QC, Canada, October 18, 2021

Shadow-Mapping for Unsupervised Neural Causal Discovery.

Matthew J. Vowels, Necati Cihan Camgöz, Richard Bowden

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

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

Matthew J. Vowels, Necati Cihan Camgöz, Richard Bowden

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

Targeted VAE: Structured Inference and Targeted Learning for Causal Parameter Estimation.

Matthew James Vowels, Necati Cihan Camgöz, Richard Bowden

CoRR, 2020

Gated Variational AutoEncoders: Incorporating Weak Supervision to Encourage Disentanglement.

Matthew J. Vowels, Necati Cihan Camgöz, Richard Bowden

Proceedings of the 15th IEEE International Conference on Automatic Face and Gesture Recognition, 2020

NestedVAE: Isolating Common Factors via Weak Supervision.

Matthew J. Vowels, Necati Cihan Camgöz, Richard Bowden

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020