Strathmann, Heiko

13 publications

ICLRW 2022 Annealed Importance Sampling Meets Score Matching Arnaud Doucet, Will Sussman Grathwohl, Alexander G. de G. Matthews, Heiko Strathmann

NeurIPS 2022 Score-Based Diffusion Meets Annealed Importance Sampling Arnaud Doucet, Will Grathwohl, Alexander G Matthews, Heiko Strathmann

ICML 2021 NeRF-VAE: A Geometry Aware 3D Scene Generative Model Adam R Kosiorek, Heiko Strathmann, Daniel Zoran, Pol Moreno, Rosalia Schneider, Sona Mokra, Danilo Jimenez Rezende

ICLRW 2021 Persistent Message Passing Heiko Strathmann, Mohammadamin Barekatain, Charles Blundell, Petar Veličković

ICML 2019 Learning Deep Kernels for Exponential Family Densities Li Wenliang, Danica J. Sutherland, Heiko Strathmann, Arthur Gretton

ICLR 2019 SOM-VAE: Interpretable Discrete Representation Learning on Time Series Vincent Fortuin, Matthias Hüser, Francesco Locatello, Heiko Strathmann, Gunnar Rätsch

AISTATS 2018 Efficient and Principled Score Estimation with Nyström Kernel Exponential Families Danica J. Sutherland, Heiko Strathmann, Michael Arbel, Arthur Gretton

ICLR 2017 Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy Danica J. Sutherland, Hsiao-Yu Tung, Heiko Strathmann, Soumyajit De, Aaditya Ramdas, Alexander J. Smola, Arthur Gretton

ECML-PKDD 2017 Kernel Sequential Monte Carlo Ingmar Schuster, Heiko Strathmann, Brooks Paige, Dino Sejdinovic

ICML 2016 A Kernel Test of Goodness of Fit Kacper Chwialkowski, Heiko Strathmann, Arthur Gretton

NeurIPS 2015 Gradient-Free Hamiltonian Monte Carlo with Efficient Kernel Exponential Families Heiko Strathmann, Dino Sejdinovic, Samuel Livingstone, Zoltan Szabo, Arthur Gretton

ICML 2014 Kernel Adaptive Metropolis-Hastings Dino Sejdinovic, Heiko Strathmann, Maria Lomeli Garcia, Christophe Andrieu, Arthur Gretton

NeurIPS 2012 Optimal Kernel Choice for Large-Scale Two-Sample Tests Arthur Gretton, Dino Sejdinovic, Heiko Strathmann, Sivaraman Balakrishnan, Massimiliano Pontil, Kenji Fukumizu, Bharath K. Sriperumbudur