Edward Meeds

According to our database, Edward Meeds authored at least 17 papers between 2005 and 2024.

Collaborative distances:

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

2024

SWAN: SGD with Normalization and Whitening Enables Stateless LLM Training.

Chao Ma, Wenbo Gong, Meyer Scetbon, Edward Meeds

CoRR, 2024

2023

AIRIVA: A Deep Generative Model of Adaptive Immune Repertoires.

Melanie F. Pradier, Niranjani Prasad, Paidamoyo Chapfuwa, Sahra Ghalebikesabi, Max Ilse, Steven Woodhouse, Rebecca Elyanow, Javier Zazo, Javier González Hernández, Julia Greissl, Edward Meeds

CoRR, 2023

AIRIVA: A Deep Generative Model of Adaptive Immune Repertoires.

Melanie F. Pradier, Niranjani Prasad, Paidamoyo Chapfuwa, Sahra Ghalebikesabi, Maximilian Ilse, Steven Woodhouse, Rebecca Elyanow, Javier Zazo, Javier González Hernández, Julia Greissl, Edward Meeds

Proceedings of the Machine Learning for Healthcare Conference, 2023

2022

Capturing actionable dynamics with structured latent ordinary differential equations.

Paidamoyo Chapfuwa, Sherri Rose, Lawrence Carin, Edward Meeds, Ricardo Henao

Proceedings of the Uncertainty in Artificial Intelligence, 2022

2019

Efficient Amortised Bayesian Inference for Hierarchical and Nonlinear Dynamical Systems.

Geoffrey Roeder, Paul K. Grant, Andrew Phillips, Neil Dalchau, Edward Meeds

Proceedings of the 36th International Conference on Machine Learning, 2019

Deterministic Variational Inference for Robust Bayesian Neural Networks.

Anqi Wu, Sebastian Nowozin, Edward Meeds, Richard E. Turner, José Miguel Hernández-Lobato, Alexander L. Gaunt

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Fixing Variational Bayes: Deterministic Variational Inference for Bayesian Neural Networks.

Anqi Wu, Sebastian Nowozin, Edward Meeds, Richard E. Turner, José Miguel Hernández-Lobato, Alexander L. Gaunt

CoRR, 2018

2017

Soft Weight-Sharing for Neural Network Compression.

Karen Ullrich, Edward Meeds, Max Welling

Proceedings of the 5th International Conference on Learning Representations, 2017

2015

MLitB: machine learning in the browser.

Edward Meeds, Remco Hendriks, Said al Faraby, Magiel Bruntink, Max Welling

PeerJ Comput. Sci., 2015

POPE: post optimization posterior evaluation of likelihood free models.

Edward Meeds, Michael Chiang, Mary Lee, Olivier Cinquin, John S. Lowengrub, Max Welling

BMC Bioinform., 2015

Hamiltonian ABC.

Edward Meeds, Robert Leenders, Max Welling

Proceedings of the Thirty-First Conference on Uncertainty in Artificial Intelligence, 2015

Optimization Monte Carlo: Efficient and Embarrassingly Parallel Likelihood-Free Inference.

Edward Meeds, Max Welling

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

2014

GPS-ABC: Gaussian Process Surrogate Approximate Bayesian Computation.

Edward Meeds, Max Welling

Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence, 2014

2008

Nonparametric Bayesian Methods for Extracting Structure from Data.

Edward Meeds

PhD thesis, 2008

Learning stick-figure models using nonparametric Bayesian priors over trees.

Edward Meeds, David A. Ross, Richard S. Zemel, Sam T. Roweis

Proceedings of the 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2008), 2008

2006

Modeling Dyadic Data with Binary Latent Factors.

Edward Meeds, Zoubin Ghahramani, Radford M. Neal, Sam T. Roweis

Proceedings of the Advances in Neural Information Processing Systems 19, 2006

2005

An Alternative Infinite Mixture Of Gaussian Process Experts.

Edward Meeds, Simon Osindero

Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005