Obserwuj
Klaus Greff
Klaus Greff
Research Scientist at Google Brain
Zweryfikowany adres z usi.ch - Strona główna
Tytuł
Cytowane przez
Cytowane przez
Rok
LSTM: A search space odyssey
K Greff, RK Srivastava, J Koutník, BR Steunebrink, J Schmidhuber
IEEE transactions on neural networks and learning systems 28 (10), 2222-2232, 2016
66492016
Training very deep networks
RK Srivastava, K Greff, J Schmidhuber
Advances in neural information processing systems 28, 2015
33072015
Highway networks
RK Srivastava, K Greff, J Schmidhuber
arXiv preprint arXiv:1505.00387, 2015
25342015
A Clockwork RNN
J Koutnik, K Greff, F Gomez, J Schmidhuber
International Conference on Machine Learning, 1863-1871, 2014
6482014
Palm-e: An embodied multimodal language model
D Driess, F Xia, MSM Sajjadi, C Lynch, A Chowdhery, B Ichter, A Wahid, ...
arXiv preprint arXiv:2303.03378, 2023
5962023
Multi-Object Representation Learning with Iterative Variational Inference
K Greff, RL Kaufman, R Kabra, N Watters, C Burgess, D Zoran, L Matthey, ...
arXiv preprint arXiv:1903.00450, 2019
4472019
Relational neural expectation maximization: Unsupervised discovery of objects and their interactions
S Van Steenkiste, M Chang, K Greff, J Schmidhuber
arXiv preprint arXiv:1802.10353, 2018
3012018
Neural Expectation Maximization
K Greff, S van Steenkiste, J Schmidhuber
Advances in Neural Information Processing Systems 30, 6694--6704, 2017
2872017
Highway and residual networks learn unrolled iterative estimation
K Greff, RK Srivastava, J Schmidhuber
arXiv preprint arXiv:1612.07771, 2016
2542016
On the binding problem in artificial neural networks
K Greff, S Van Steenkiste, J Schmidhuber
arXiv preprint arXiv:2012.05208, 2020
2192020
Scalable Gradient-Based Tuning of Continuous Regularization Hyperparameters
J Luketina, M Berglund, K Greff, T Raiko
arXiv preprint, 2015
1892015
Tagger: Deep unsupervised perceptual grouping
K Greff, A Rasmus, M Berglund, T Hao, H Valpola, J Schmidhuber
Advances in Neural Information Processing Systems 29, 2016
1652016
Conditional object-centric learning from video
T Kipf, GF Elsayed, A Mahendran, A Stone, S Sabour, G Heigold, ...
arXiv preprint arXiv:2111.12594, 2021
1422021
Scene representation transformer: Geometry-free novel view synthesis through set-latent scene representations
MSM Sajjadi, H Meyer, E Pot, U Bergmann, K Greff, N Radwan, S Vora, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
1062022
The sacred infrastructure for computational research
K Greff, A Klein, M Chovanec, F Hutter, J Schmidhuber
Proceedings of the 16th python in science conference 28, 49-56, 2017
972017
Kubric: A scalable dataset generator
K Greff, F Belletti, L Beyer, C Doersch, Y Du, D Duckworth, DJ Fleet, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022
952022
Highway networks. arXiv 2015
RK Srivastava, K Greff, J Schmidhuber
arXiv preprint arXiv:1505.00387, 2015
772015
Savi++: Towards end-to-end object-centric learning from real-world videos
G Elsayed, A Mahendran, S van Steenkiste, K Greff, MC Mozer, T Kipf
Advances in Neural Information Processing Systems 35, 28940-28954, 2022
762022
Nesf: Neural semantic fields for generalizable semantic segmentation of 3d scenes
S Vora, N Radwan, K Greff, H Meyer, K Genova, MSM Sajjadi, E Pot, ...
arXiv preprint arXiv:2111.13260, 2021
652021
Multi-object datasets
R Kabra, C Burgess, L Matthey, RL Kaufman, K Greff, M Reynolds, ...
DeepMind 5 (6), 7, 2019
652019
Nie można teraz wykonać tej operacji. Spróbuj ponownie później.
Prace 1–20