Edward Meeds - researchr alias

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Viewing Publication 1 - 14 from 14

2023

AIRIVA: A Deep Generative Model of Adaptive Immune RepertoiresMelanie F. Pradier, Niranjani Prasad, Paidamoyo Chapfuwa, Sahra Ghalebikesabi, Maximilian Ilse, Steven Woodhouse, Rebecca Elyanow, Javier Zazo, Javier González Hernández, Julia Greissl, Edward Meeds. mlhc 2023: 588-611 [doi]

2022

Capturing actionable dynamics with structured latent ordinary differential equationsPaidamoyo Chapfuwa, Sherri Rose, Lawrence Carin, Edward Meeds, Ricardo Henao. uai 2022: 286-295 [doi]

2019

Efficient Amortised Bayesian Inference for Hierarchical and Nonlinear Dynamical SystemsGeoffrey Roeder, Paul K. Grant, Andrew Phillips, Neil Dalchau, Edward Meeds. icml 2019: 4445-4455 [doi]

Deterministic Variational Inference for Robust Bayesian Neural NetworksAnqi Wu, Sebastian Nowozin, Edward Meeds, Richard E. Turner, José Miguel Hernández-Lobato, Alexander L. Gaunt. iclr 2019: [doi]

2017

Soft Weight-Sharing for Neural Network CompressionKaren Ullrich, Edward Meeds, Max Welling. iclr 2017: [doi]

2015

2014

GPS-ABC: Gaussian Process Surrogate Approximate Bayesian ComputationEdward Meeds, Max Welling. uai 2014: 593-602 [doi]

2008

Nonparametric Bayesian Methods for Extracting Structure from DataEdward Meeds. PhD thesis, University of Toronto, Canada, 2008. [doi]

Learning stick-figure models using nonparametric Bayesian priors over treesEdward Meeds, David A. Ross, Richard S. Zemel, Sam T. Roweis. cvpr 2008: [doi]

2006

Modeling Dyadic Data with Binary Latent FactorsEdward Meeds, Zoubin Ghahramani, Radford M. Neal, Sam T. Roweis. nips 2007: 977-984 [doi]

2005

An Alternative Infinite Mixture Of Gaussian Process ExpertsEdward Meeds, Simon Osindero. nips 2005: 883-890 [doi]

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