Holmes, Chris

13 publications

AAAI 2025 Fields of the World: A Machine Learning Benchmark Dataset for Global Agricultural Field Boundary Segmentation Hannah Kerner, Snehal Chaudhari, Aninda Ghosh, Caleb Robinson, Adeel Ahmad, Eddie Choi, Nathan Jacobs, Chris Holmes, Matthias Mohr, Rahul Dodhia, Juan M. Lavista Ferres, Jennifer Marcus

UAI 2024 Towards Representation Learning for Weighting Problems in Design-Based Causal Inference Oscar Clivio, Avi Feller, Chris Holmes

AISTATS 2022 Neural Score Matching for High-Dimensional Causal Inference Oscar Clivio, Fabian Falck, Brieuc Lehmann, George Deligiannidis, Chris Holmes

UAI 2022 Mitigating Statistical Bias Within Differentially Private Synthetic Data Sahra Ghalebikesabi, Harry Wilde, Jack Jewson, Arnaud Doucet, Sebastian Vollmer, Chris Holmes

AISTATS 2021 Deep Generative Missingness Pattern-Set Mixture Models Sahra Ghalebikesabi, Rob Cornish, Chris Holmes, Luke Kelly

AISTATS 2021 Foundations of Bayesian Learning from Synthetic Data Harrison Wilde, Jack Jewson, Sebastian Vollmer, Chris Holmes

AISTATS 2021 Learning Bijective Feature Maps for Linear ICA Alexander Camuto, Matthew Willetts, Chris Holmes, Brooks Paige, Stephen Roberts

AISTATS 2021 Towards a Theoretical Understanding of the Robustness of Variational Autoencoders Alexander Camuto, Matthew Willetts, Stephen Roberts, Chris Holmes, Tom Rainforth

ICML 2021 Asymmetric Heavy Tails and Implicit Bias in Gaussian Noise Injections Alexander Camuto, Xiaoyu Wang, Lingjiong Zhu, Chris Holmes, Mert Gurbuzbalaban, Umut Simsekli

ICML 2019 Scalable Nonparametric Sampling from Multimodal Posteriors with the Posterior Bootstrap Edwin Fong, Simon Lyddon, Chris Holmes

ICML 2018 Probabilistic Boolean Tensor Decomposition Tammo Rukat, Chris Holmes, Christopher Yau

JMLR 2017 On Markov Chain Monte Carlo Methods for Tall Data Rémi Bardenet, Arnaud Doucet, Chris Holmes

ICML 2014 Towards Scaling up Markov Chain Monte Carlo: An Adaptive Subsampling Approach Rémi Bardenet, Arnaud Doucet, Chris Holmes