Heiko Strathmann

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 20

Top Topics

Generative Model

Top Venues

Publications

SIMA Team, Maria Abi Raad, Arun Ahuja, Catarina Barros, Frederic Besse, Andrew Bolt, Adrian Bolton, Bethanie Brownfield, Gavin Buttimore, Max Cant, Sarah Chakera, Stephanie C. Y. Chan, Jeff Clune, Adrian Collister, Vikki Copeman, Alex Cullum, Ishita Dasgupta, Dario de Cesare, Julia Di Trapani, Yani Donchev, Emma Dunleavy, Martin Engelcke, Ryan Faulkner, Frankie Garcia, Charles Gbadamosi, Zhitao Gong, Lucy Gonzalez, Kshitij Gupta, Karol Gregor, Arne Olav Hallingstad, Tim Harley, Sam Haves, Felix Hill, Ed Hirst, Drew A. Hudson, Jony Hudson, Steph Hughes-Fitt, Danilo J. Rezende, Mimi Jasarevic, Laura Kampis, Nan Rosemary Ke, Thomas Keck, Junkyung Kim, Oscar Knagg, Kavya Kopparapu, Andrew K. Lampinen, Shane Legg, Alexander Lerchner, Marjorie Limont, Yulan Liu, Maria Loks-Thompson, Joseph Marino, Kathryn Martin Cussons, Loic Matthey, Siobhan Mcloughlin, Piermaria Mendolicchio, Hamza Merzic, Anna Mitenkova, Alexandre Moufarek, Valéria Oliveira, Yanko Gitahy Oliveira, Hannah Openshaw, Renke Pan, Aneesh Pappu, Alex Platonov, Ollie Purkiss, David P. Reichert, John Reid, Pierre Harvey Richemond, Tyson Roberts, Giles Ruscoe, Jaume Sanchez Elias, Tasha Sandars, Daniel P. Sawyer, Tim Scholtes, Guy Simmons, Daniel Slater, Hubert Soyer, Heiko Strathmann, Peter Stys, Allison C. Tam, Denis Teplyashin, Tayfun Terzi, Davide Vercelli, Bojan Vujatovic, Marcus Wainwright, Jane X. Wang, Zhengdong Wang, Daan Wierstra, Duncan Williams, Nathaniel Wong, Sarah York, Nick Young
Scaling Instructable Agents Across Many Simulated Worlds. CoRR (2024)
Pol Moreno, Adam R. Kosiorek, Heiko Strathmann, Daniel Zoran, Rosália G. Schneider, Björn Winckler, Larisa Markeeva, Théophane Weber, Danilo J. Rezende
Laser: Latent Set Representations for 3D Generative Modeling. CoRR (2023)
Arnaud Doucet, Will Grathwohl, Alexander G. de G. Matthews, Heiko Strathmann
Score-Based Diffusion meets Annealed Importance Sampling. CoRR (2022)
Arnaud Doucet, Will Grathwohl, Alexander G. de G. Matthews, Heiko Strathmann
Score-Based Diffusion meets Annealed Importance Sampling. NeurIPS (2022)
Vincent Fortuin, Gideon Dresdner, Heiko Strathmann, Gunnar Rätsch
Sparse Gaussian Processes on Discrete Domains. IEEE Access 9 (2021)
Adam R. Kosiorek, Heiko Strathmann, Daniel Zoran, Pol Moreno, Rosalia Schneider, Sona Mokrá, Danilo J. Rezende
NeRF-VAE: A Geometry Aware 3D Scene Generative Model. CoRR (2021)
Heiko Strathmann, Mohammadamin Barekatain, Charles Blundell, Petar Velickovic
Persistent Message Passing. CoRR (2021)
Lauro Langosco di Langosco, Vincent Fortuin, Heiko Strathmann
Neural Variational Gradient Descent. CoRR (2021)
Adam R. Kosiorek, Heiko Strathmann, Daniel Zoran, Pol Moreno, Rosalia Schneider, Sona Mokrá, Danilo Jimenez Rezende
NeRF-VAE: A Geometry Aware 3D Scene Generative Model. ICML (2021)
Vincent Fortuin, Matthias Hüser, Francesco Locatello, Heiko Strathmann, Gunnar Rätsch
SOM-VAE: Interpretable Discrete Representation Learning on Time Series. ICLR (Poster) (2019)
Wenliang Li, Danica J. Sutherland, Heiko Strathmann, Arthur Gretton
Learning deep kernels for exponential family densities. ICML (2019)
Danica J. Sutherland, Heiko Strathmann, Michael Arbel, Arthur Gretton
Efficient and principled score estimation with Nyström kernel exponential families. AISTATS (2018)
Vincent Fortuin, Gideon Dresdner, Heiko Strathmann, Gunnar Rätsch
Scalable Gaussian Processes on Discrete Domains. CoRR (2018)
Wenliang Li, Danica J. Sutherland, Heiko Strathmann, Arthur Gretton
Learning deep kernels for exponential family densities. CoRR (2018)
Vincent Fortuin, Matthias Hüser, Francesco Locatello, Heiko Strathmann, Gunnar Rätsch
Deep Self-Organization: Interpretable Discrete Representation Learning on Time Series. CoRR (2018)
Danica J. Sutherland, Heiko Strathmann, Michael Arbel, Arthur Gretton
Efficient and principled score estimation. CoRR (2017)
Ingmar Schuster, Heiko Strathmann, Brooks Paige, Dino Sejdinovic
Kernel Sequential Monte Carlo. ECML/PKDD (1) (2017)
Danica J. Sutherland, Hsiao-Yu Tung, Heiko Strathmann, Soumyajit De, Aaditya Ramdas, Alexander J. Smola, Arthur Gretton
Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy. ICLR (Poster) (2017)
Kacper Chwialkowski, Heiko Strathmann, Arthur Gretton
A Kernel Test of Goodness of Fit. ICML (2016)
Danica J. Sutherland, Hsiao-Yu Fish Tung, Heiko Strathmann, Soumyajit De, Aaditya Ramdas, Alexander J. Smola, Arthur Gretton
Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy. CoRR (2016)
Heiko Strathmann, Dino Sejdinovic, Samuel Livingstone, Zoltán Szabó, Arthur Gretton
Gradient-free Hamiltonian Monte Carlo with Efficient Kernel Exponential Families. NIPS (2015)
Heiko Strathmann, Dino Sejdinovic, Mark A. Girolami
Unbiased Bayes for Big Data: Paths of Partial Posteriors. CoRR (2015)
Dino Sejdinovic, Heiko Strathmann, Maria Lomeli Garcia, Christophe Andrieu, Arthur Gretton
Kernel Adaptive Metropolis-Hastings. ICML (2014)
Dino Sejdinovic, Maria Lomeli Garcia, Heiko Strathmann, Christophe Andrieu, Arthur Gretton
Kernel Adaptive Metropolis-Hastings. CoRR (2013)
Arthur Gretton, Bharath K. Sriperumbudur, Dino Sejdinovic, Heiko Strathmann, Sivaraman Balakrishnan, Massimiliano Pontil, Kenji Fukumizu
Optimal kernel choice for large-scale two-sample tests. NIPS (2012)