McInerney, James

10 publications

AISTATS 2025 Variation Due to Regularization Tractably Recovers Bayesian Deep Learning Uncertainty James McInerney, Nathan Kallus

MLJ 2024 Adjusting Regression Models for Conditional Uncertainty Calibration Ruijiang Gao, Mingzhang Yin, James McInerney, Nathan Kallus

ICML 2024 Switching the Loss Reduces the Cost in Batch Reinforcement Learning Alex Ayoub, Kaiwen Wang, Vincent Liu, Samuel Robertson, James Mcinerney, Dawen Liang, Nathan Kallus, Csaba Szepesvari

NeurIPSW 2023 Hessian-Free Laplace in Bayesian Deep Learning James McInerney, Nathan Kallus

NeurIPS 2022 The Implicit Delta Method Nathan Kallus, James McInerney

NeurIPS 2017 An Empirical Bayes Approach to Optimizing Machine Learning Algorithms James McInerney

AISTATS 2016 Variational Tempering Stephan Mandt, James McInerney, Farhan Abrol, Rajesh Ranganath, David M. Blei

NeurIPS 2015 The Population Posterior and Bayesian Modeling on Streams James McInerney, Rajesh Ranganath, David Blei

IJCAI 2013 Forecasting Multi-Appliance Usage for Smart Home Energy Management Ngoc Cuong Truong, James McInerney, Long Tran-Thanh, Enrico Costanza, Sarvapali D. Ramchurn

UAI 2013 Learning Periodic Human Behaviour Models from Sparse Data for Crowdsourcing Aid Delivery in Developing Countries James McInerney, Alex Rogers, Nicholas R. Jennings