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Sjoerd van Steenkiste
Sjoerd van Steenkiste
Research Scientist at Google Research
Zweryfikowany adres z google.com - Strona główna
Tytuł
Cytowane przez
Cytowane przez
Rok
Relational Neural Expectation Maximization: Unsupervised Discovery of Objects and their Interactions
S van Steenkiste, M Chang, K Greff, J Schmidhuber
International Conference on Learning Representations, 2018
2532018
Neural Expectation Maximization
K Greff*, S van Steenkiste*, J Schmidhuber
Advances in Neural Information Processing Systems 30, 6694--6704, 2017
2282017
Towards Accurate Generative Models of Video: A New Metric & Challenges
T Unterthiner*, S van Steenkiste*, K Kurach, R Marinier, M Michalski, ...
arXiv preprint arXiv:1812.01717, 2018
1472018
Are Disentangled Representations Helpful for Abstract Visual Reasoning?
S van Steenkiste, F Locatello, J Schmidhuber, O Bachem
Advances in Neural Information Processing Systems 32, 14222--14235, 2019
1302019
On the binding problem in artificial neural networks
K Greff, S Van Steenkiste, J Schmidhuber
arXiv preprint arXiv:2012.05208, 2020
1172020
Improving Generalization in Meta Reinforcement Learning using Learned Objectives
L Kirsch, S van Steenkiste, J Schmidhuber
International Conference on Learning Representations, 2020
782020
Investigating object compositionality in generative adversarial networks
S van Steenkiste, K Kurach, J Schmidhuber, S Gelly
Neural Networks 130, 309-325, 2020
44*2020
Are Neural Nets Modular? Inspecting Functional Modularity Through Differentiable Weight Masks
R Csordás, S van Steenkiste, J Schmidhuber
International Conference on Learning Representations, 2021
32*2021
A Wavelet-based Encoding for Neuroevolution
S van Steenkiste, J Koutník, K Driessens, J Schmidhuber
Proceedings of the Genetic and Evolutionary Computation Conference 2016, 517-524, 2016
192016
Unsupervised Object Keypoint Learning using Local Spatial Predictability
A Gopalakrishnan, S van Steenkiste, J Schmidhuber
International Conference on Learning Representations, 2021
162021
A Perspective on Objects and Systematic Generalization in Model-Based RL
S van Steenkiste*, K Greff*, J Schmidhuber
ICML Workshop on Generative Modeling and Model-Based Reasoning for Robotics …, 2019
162019
FVD: A new Metric for Video Generation
T Unterthiner*, S van Steenkiste*, K Kurach, R Marinier, M Michalski, ...
ICLR Workshop on Deep Generative Models for Highly Structured Data, 2019
162019
Hierarchical Relational Inference
A Stanić, S van Steenkiste, J Schmidhuber
Proceedings of the AAAI Conference on Artificial Intelligence 35 (11), 9730 …, 2021
152021
Savi++: Towards end-to-end object-centric learning from real-world videos
GF Elsayed*, A Mahendran*, S van Steenkiste*, K Greff, MC Mozer, ...
arXiv preprint arXiv:2206.07764, 2022
72022
Object Scene Representation Transformer
MSM Sajjadi, D Duckworth*, A Mahendran*, S van Steenkiste*, F Pavetić, ...
arXiv preprint arXiv:2206.06922, 2022
52022
Unsupervised Learning of Temporal Abstractions with Slot-based Transformers
A Gopalakrishnan, K Irie, J Schmidhuber, S van Steenkiste
NeurIPS Workshop on Offline Reinforcement Learning & NeurIPS Workshop on …, 2021
12021
Learning structured neural representations for visual reasoning tasks
S van Steenkiste
Università della Svizzera italiana, 2020
12020
Spatial Symmetry in Slot Attention
O Biza, S van Steenkiste, MSM Sajjadi, GF Elsayed, A Mahendran, T Kipf
NeurIPS 2022 Workshop on Symmetry and Geometry in Neural Representations, 2022
2022
Test-time adaptation with slot-centric models
M Prabhudesai, S Paul, S van Steenkiste, MSM Sajjadi, A Goyal, ...
NeurIPS 2022 Workshop on Distribution Shifts: Connecting Methods and …, 2022
2022
Exploring through Random Curiosity with General Value Functions
A Ramesh, L Kirsch, S van Steenkiste, J Schmidhuber
arXiv preprint arXiv:2211.10282, 2022
2022
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