Edward Meeds - RankMe

28 papers A* 3A 3Journal 15Unranked 6

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	A Fourier Space Perspective on Diffusion Models. CoRR Fabian Falck, Teodora Pandeva, Kiarash Zahirnia, Rachel Lawrence, Richard E. Turner, Edward Meeds, Javier Zazo, Sushrut Karmalkar
2025	J	`jnl`	Gradient Multi-Normalization for Stateless and Scalable LLM Training. CoRR Meyer Scetbon, Chao Ma, Wenbo Gong, Edward Meeds
2025	A*	`conf`	SWAN: SGD with Normalization and Whitening Enables Stateless LLM Training. ICML Chao Ma, Wenbo Gong, Meyer Scetbon, Edward Meeds
2025	J	`jnl`	Towards Efficient Optimizer Design for LLM via Structured Fisher Approximation with a Low-Rank Extension. CoRR Wenbo Gong, Meyer Scetbon, Chao Ma, Edward Meeds
2024	J	`jnl`	SWAN: SGD with Normalization and Whitening Enables Stateless LLM Training. CoRR Chao Ma, Wenbo Gong, Meyer Scetbon, Edward Meeds
2023	—	`conf`	AIRIVA: A Deep Generative Model of Adaptive Immune Repertoires. MLHC Melanie F. Pradier, Niranjani Prasad, Paidamoyo Chapfuwa, Sahra Ghalebikesabi, Maximilian Ilse, Steven Woodhouse, Rebecca Elyanow, Javier Zazo, Javier González Hernández, Julia Greissl, Edward Meeds
2023	J	`jnl`	AIRIVA: A Deep Generative Model of Adaptive Immune Repertoires. CoRR Melanie F. Pradier, Niranjani Prasad, Paidamoyo Chapfuwa, Sahra Ghalebikesabi, Max Ilse, Steven Woodhouse, Rebecca Elyanow, Javier Zazo, Javier González Hernández, Julia Greissl, Edward Meeds
2022	J	`jnl`	Capturing Actionable Dynamics with Structured Latent Ordinary Differential Equations. CoRR Paidamoyo Chapfuwa, Sherri Rose, Lawrence Carin, Edward Meeds, Ricardo Henao
2022	A	`conf`	Capturing actionable dynamics with structured latent ordinary differential equations. UAI Paidamoyo Chapfuwa, Sherri Rose, Lawrence Carin, Edward Meeds, Ricardo Henao
2019	—	`conf`	Deterministic Variational Inference for Robust Bayesian Neural Networks. ICLR Anqi Wu, Sebastian Nowozin, Edward Meeds, Richard E. Turner, José Miguel Hernández-Lobato, Alexander L. Gaunt
2019	A*	`conf`	Efficient Amortised Bayesian Inference for Hierarchical and Nonlinear Dynamical Systems. ICML Geoffrey Roeder, Paul K. Grant, Andrew Phillips, Neil Dalchau, Edward Meeds
2019	J	`jnl`	Efficient Amortised Bayesian Inference for Hierarchical and Nonlinear Dynamical Systems. CoRR Geoffrey Roeder, Paul K. Grant, Andrew Phillips, Neil Dalchau, Edward Meeds
2018	J	`jnl`	Fixing Variational Bayes: Deterministic Variational Inference for Bayesian Neural Networks. CoRR Anqi Wu, Sebastian Nowozin, Edward Meeds, Richard E. Turner, José Miguel Hernández-Lobato, Alexander L. Gaunt
2017	—	`conf`	Soft Weight-Sharing for Neural Network Compression. ICLR (Poster) Karen Ullrich, Edward Meeds, Max Welling
2017	J	`jnl`	Soft Weight-Sharing for Neural Network Compression. CoRR Karen Ullrich, Edward Meeds, Max Welling
2015	A	`conf`	Hamiltonian ABC. UAI Edward Meeds, Robert Leenders, Max Welling
2015	J	`jnl`	Hamiltonian ABC. CoRR Edward Meeds, Robert Leenders, Max Welling
2015	J	`jnl`	MLitB: machine learning in the browser. PeerJ Comput. Sci. Edward Meeds, Remco Hendriks, Said al Faraby, Magiel Bruntink, Max Welling
2015	—	`conf`	Optimization Monte Carlo: Efficient and Embarrassingly Parallel Likelihood-Free Inference. NIPS Edward Meeds, Max Welling
2015	J	`jnl`	Optimization Monte Carlo: Efficient and Embarrassingly Parallel Likelihood-Free Inference. CoRR Edward Meeds, Max Welling
2015	J	`jnl`	POPE: post optimization posterior evaluation of likelihood free models. BMC Bioinform. Edward Meeds, Michael Chiang, Mary Lee, Olivier Cinquin, John S. Lowengrub, Max Welling
2014	A	`conf`	GPS-ABC: Gaussian Process Surrogate Approximate Bayesian Computation. UAI Edward Meeds, Max Welling
2014	J	`jnl`	GPS-ABC: Gaussian Process Surrogate Approximate Bayesian Computation. CoRR Edward Meeds, Max Welling
2014	J	`jnl`	MLitB: Machine Learning in the Browser. CoRR Edward Meeds, Remco Hendriks, Said al Faraby, Magiel Bruntink, Max Welling
2008	A*	`conf`	Learning stick-figure models using nonparametric Bayesian priors over trees. CVPR Edward Meeds, David A. Ross, Richard S. Zemel, Sam T. Roweis
2008	—	`—`	Nonparametric Bayesian Methods for Extracting Structure from Data. Edward Meeds
2006	—	`conf`	Modeling Dyadic Data with Binary Latent Factors. NIPS Edward Meeds, Zoubin Ghahramani, Radford M. Neal, Sam T. Roweis
2005	—	`conf`	An Alternative Infinite Mixture Of Gaussian Process Experts. NIPS Edward Meeds, Simon Osindero