Alex Markham

According to our database, Alex Markham authored at least 12 papers between 2020 and 2024.

Collaborative distances:

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

2024

Scalable Structure Learning for Sparse Context-Specific Causal Systems.

Felix Leopoldo Rios, Alex Markham, Liam Solus

CoRR, 2024

2023

Neuro-Causal Factor Analysis.

Alex Markham, Mingyu Liu, Bryon Aragam, Liam Solus

CoRR, 2023

Queer In AI: A Case Study in Community-Led Participatory AI.

Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J. Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi Jethwani, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx McLean, Pan Xu, Pranav A, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J. Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y. Bilenko, Andrew McNamara, Raphael Gontijo Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, Luke Stark

CoRR, 2023

Queer In AI: A Case Study in Community-Led Participatory AI.

Organizers Of QueerInAI, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J. Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi Jethwani, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx McLean, Pan Xu, Pranav A, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J. Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y. Bilenko, Andrew McNamara, Raphael Gontijo Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, Luke Stark

Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023

2022

Causal Structure Learning with Greedy Unconditional Equivalence Search.

Alex Markham, Danai Deligeorgaki, Pratik Misra, Liam Solus

CoRR, 2022

A Transformational Characterization of Unconditionally Equivalent Bayesian Networks.

Alex Markham, Danai Deligeorgaki, Pratik Misra, Liam Solus

Proceedings of the International Conference on Probabilistic Graphical Models, 2022

A Distance Covariance-based Kernel for Nonlinear Causal Clustering in Heterogeneous Populations.

Alex Markham, Richeek Das, Moritz Grosse-Wentrup

Proceedings of the 1st Conference on Causal Learning and Reasoning, 2022

2021

A Distance Covariance-based Kernel for Nonlinear Causal Clustering in Heterogeneous Populations.

Alex Markham, Moritz Grosse-Wentrup

CoRR, 2021

Distance Covariance: A Nonlinear Extension of Riemannian Geometry for EEG-based Brain-Computer Interfacing.

Jiachen Xu, Alex Markham, Anja Meunier, Philipp Raggam, Moritz Grosse-Wentrup

Proceedings of the 2021 IEEE International Conference on Systems, Man, and Cybernetics, 2021

A theory of algorithms and implementations and their relevance to cognitive science.

Anja Meunier, Alex Markham, Moritz Grosse-Wentrup

Proceedings of the 43th Annual Meeting of the Cognitive Science Society, 2021

2020

Measurement Dependence Inducing Latent Causal Models.

Alex Markham, Moritz Grosse-Wentrup

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

MeDIL: A Python Package for Causal Modelling.

Alex Markham, Aditya Chivukula, Moritz Grosse-Wentrup

Proceedings of the International Conference on Probabilistic Graphical Models, 2020