Klaus Greff

According to our database, Klaus Greff authored at least 31 papers between 2012 and 2023.

Collaborative distances:

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

2023

Getting aligned on representational alignment.

Ilia Sucholutsky, Lukas Muttenthaler, Adrian Weller, Andi Peng, Andreea Bobu, Been Kim, Bradley C. Love, Erin Grant, Jascha Achterberg, Joshua B. Tenenbaum, Katherine M. Collins, Katherine L. Hermann, Kerem Oktar, Klaus Greff, Martin N. Hebart, Nori Jacoby, Qiuyi Zhang, Raja Marjieh, Robert Geirhos, Sherol Chen, Simon Kornblith, Sunayana Rane, Talia Konkle, Thomas P. O'Connell, Thomas Unterthiner, Andrew K. Lampinen, Klaus-Robert Müller, Mariya Toneva, Thomas L. Griffiths

CoRR, 2023

DyST: Towards Dynamic Neural Scene Representations on Real-World Videos.

Maximilian Seitzer, Sjoerd van Steenkiste, Thomas Kipf, Klaus Greff, Mehdi S. M. Sajjadi

CoRR, 2023

Sensitivity of Slot-Based Object-Centric Models to their Number of Slots.

Roland S. Zimmermann, Sjoerd van Steenkiste, Mehdi S. M. Sajjadi, Thomas Kipf, Klaus Greff

CoRR, 2023

PaLM-E: An Embodied Multimodal Language Model.

Danny Driess, Fei Xia, Mehdi S. M. Sajjadi, Corey Lynch, Aakanksha Chowdhery, Brian Ichter, Ayzaan Wahid, Jonathan Tompson, Quan Vuong, Tianhe Yu, Wenlong Huang, Yevgen Chebotar, Pierre Sermanet, Daniel Duckworth, Sergey Levine, Vincent Vanhoucke, Karol Hausman, Marc Toussaint, Klaus Greff, Andy Zeng, Igor Mordatch, Pete Florence

Proceedings of the International Conference on Machine Learning, 2023

SlotFormer: Unsupervised Visual Dynamics Simulation with Object-Centric Models.

Ziyi Wu, Nikita Dvornik, Klaus Greff, Thomas Kipf, Animesh Garg

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Audioslots: A Slot-Centric Generative Model For Audio Separation.

Pradyumna Reddy, Scott Wisdom, Klaus Greff, John R. Hershey, Thomas Kipf

Proceedings of the IEEE International Conference on Acoustics, 2023

RUST: Latent Neural Scene Representations from Unposed Imagery.

Mehdi S. M. Sajjadi, Aravindh Mahendran, Thomas Kipf, Etienne Pot, Daniel Duckworth, Mario Lucic, Klaus Greff

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

NeSF: Neural Semantic Fields for Generalizable Semantic Segmentation of 3D Scenes.

Suhani Vora, Noha Radwan, Klaus Greff, Henning Meyer, Kyle Genova, Mehdi S. M. Sajjadi, Etienne Pot, Andrea Tagliasacchi, Daniel Duckworth

Trans. Mach. Learn. Res., 2022

Object Scene Representation Transformer.

Mehdi S. M. Sajjadi, Daniel Duckworth, Aravindh Mahendran, Sjoerd van Steenkiste, Filip Pavetic, Mario Lucic, Leonidas J. Guibas, Klaus Greff, Thomas Kipf

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

SAVi++: Towards End-to-End Object-Centric Learning from Real-World Videos.

Gamaleldin F. Elsayed, Aravindh Mahendran, Sjoerd van Steenkiste, Klaus Greff, Michael C. Mozer, Thomas Kipf

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Conditional Object-Centric Learning from Video.

Thomas Kipf, Gamaleldin Fathy Elsayed, Aravindh Mahendran, Austin Stone, Sara Sabour, Georg Heigold, Rico Jonschkowski, Alexey Dosovitskiy, Klaus Greff

Proceedings of the Tenth International Conference on Learning Representations, 2022

Scene Representation Transformer: Geometry-Free Novel View Synthesis Through Set-Latent Scene Representations.

Mehdi S. M. Sajjadi, Henning Meyer, Etienne Pot, Urs Bergmann, Klaus Greff, Noha Radwan, Suhani Vora, Mario Lucic, Daniel Duckworth, Alexey Dosovitskiy, Jakob Uszkoreit, Thomas A. Funkhouser, Andrea Tagliasacchi

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

Kubric: A scalable dataset generator.

Klaus Greff, Francois Belletti, Lucas Beyer, Carl Doersch, Yilun Du, Daniel Duckworth, David J. Fleet, Dan Gnanapragasam, Florian Golemo, Charles Herrmann, Thomas Kipf, Abhijit Kundu, Dmitry Lagun, Issam H. Laradji, Hsueh-Ti Derek Liu, Henning Meyer, Yishu Miao, Derek Nowrouzezahrai, A. Cengiz Öztireli, Etienne Pot, Noha Radwan, Daniel Rebain, Sara Sabour, Mehdi S. M. Sajjadi, Matan Sela, Vincent Sitzmann, Austin Stone, Deqing Sun, Suhani Vora, Ziyu Wang, Tianhao Wu, Kwang Moo Yi, Fangcheng Zhong, Andrea Tagliasacchi

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2020

On the Binding Problem in Artificial Neural Networks.

Klaus Greff, Sjoerd van Steenkiste, Jürgen Schmidhuber

CoRR, 2020

Learning Object-Centric Video Models by Contrasting Sets.

Sindy Löwe, Klaus Greff, Rico Jonschkowski, Alexey Dosovitskiy, Thomas Kipf

CoRR, 2020

2019

A Perspective on Objects and Systematic Generalization in Model-Based RL.

Sjoerd van Steenkiste, Klaus Greff, Jürgen Schmidhuber

CoRR, 2019

Multi-Object Representation Learning with Iterative Variational Inference.

Klaus Greff, Raphaël Lopez Kaufman, Rishabh Kabra, Nick Watters, Chris Burgess, Daniel Zoran, Loic Matthey, Matthew M. Botvinick, Alexander Lerchner

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

2018

Relational Neural Expectation Maximization: Unsupervised Discovery of Objects and their Interactions.

Sjoerd van Steenkiste, Michael Chang, Klaus Greff, Jürgen Schmidhuber

Proceedings of the 6th International Conference on Learning Representations, 2018

2017

LSTM: A Search Space Odyssey.

Klaus Greff, Rupesh Kumar Srivastava, Jan Koutník, Bas R. Steunebrink, Jürgen Schmidhuber

IEEE Trans. Neural Networks Learn. Syst., 2017

The Sacred Infrastructure for Computational Research.

Klaus Greff, Aaron Klein, Martin Chovanec, Frank Hutter, Jürgen Schmidhuber

Proceedings of the 16th Python in Science Conference 2017, 2017

Neural Expectation Maximization.

Klaus Greff, Sjoerd van Steenkiste, Jürgen Schmidhuber

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Highway and Residual Networks learn Unrolled Iterative Estimation.

Klaus Greff, Rupesh Kumar Srivastava, Jürgen Schmidhuber

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

2016

Discovering Boolean Gates in Slime Mould.

Simon Harding, Jan Koutník, Klaus Greff, Jürgen Schmidhuber, Andy Adamatzky

CoRR, 2016

Tagger: Deep Unsupervised Perceptual Grouping.

Klaus Greff, Antti Rasmus, Mathias Berglund, Tele Hotloo Hao, Harri Valpola, Jürgen Schmidhuber

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Scalable Gradient-Based Tuning of Continuous Regularization Hyperparameters.

Jelena Luketina, Tapani Raiko, Mathias Berglund, Klaus Greff

Proceedings of the 33nd International Conference on Machine Learning, 2016

2015

Highway Networks.

Rupesh Kumar Srivastava, Klaus Greff, Jürgen Schmidhuber

CoRR, 2015

Binding via Reconstruction Clustering.

Klaus Greff, Rupesh Kumar Srivastava, Jürgen Schmidhuber

CoRR, 2015

Training Very Deep Networks.

Rupesh Kumar Srivastava, Klaus Greff, Jürgen Schmidhuber

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

2014

A Clockwork RNN.

Jan Koutník, Klaus Greff, Faustino J. Gomez, Jürgen Schmidhuber

Proceedings of the 31th International Conference on Machine Learning, 2014

2012

Visual Steering and Verification of Mass Spectrometry Data Factorization in Air Quality Research.

Daniel Engel, Klaus Greff, Christoph Garth, Keith Bein, Anthony S. Wexler, Bernd Hamann, Hans Hagen

IEEE Trans. Vis. Comput. Graph., 2012

A Comparison between Background Subtraction Algorithms using a Consumer Depth Camera.

Klaus Greff, André Brandão, Stephan Krauß, Didier Stricker, Esteban Clua

Proceedings of the VISAPP 2012, 2012