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Yulia Rubanova
Yulia Rubanova
Google Deepmind
在 google.com 的电子邮件经过验证 - 首页
标题
引用次数
引用次数
年份
Neural ordinary differential equations
RTQ Chen, Y Rubanova, J Bettencourt, DK Duvenaud
Advances in neural information processing systems 31, 2018
50832018
Pan-cancer analysis of whole genomes
Nature 578 (7793), 82-93, 2020
1794*2020
The evolutionary history of 2,658 cancers
M Gerstung, C Jolly, I Leshchiner, SC Dentro, S Gonzalez, D Rosebrock, ...
Nature 578 (7793), 122-128, 2020
9152020
Latent ordinary differential equations for irregularly-sampled time series
Y Rubanova, RTQ Chen, DK Duvenaud
Advances in neural information processing systems 32, 2019
8512019
Characterizing genetic intra-tumor heterogeneity across 2,658 human cancer genomes
SC Dentro, I Leshchiner, K Haase, M Tarabichi, J Wintersinger, ...
Cell 184 (8), 2239-2254. e39, 2021
3192021
The evolutionary landscape of localized prostate cancers drives clinical aggression
SMG Espiritu, LY Liu, Y Rubanova, V Bhandari, EM Holgersen, LM Szyca, ...
Cell 173 (4), 1003-1013. e15, 2018
2362018
Simple gnn regularisation for 3d molecular property prediction & beyond
J Godwin, M Schaarschmidt, A Gaunt, A Sanchez-Gonzalez, Y Rubanova, ...
arXiv preprint arXiv:2106.07971, 2021
1122021
A generalist neural algorithmic learner
B Ibarz, V Kurin, G Papamakarios, K Nikiforou, M Bennani, R Csordás, ...
Learning on graphs conference, 2: 1-2: 23, 2022
562022
Reconstructing evolutionary trajectories of mutation signature activities in cancer using TrackSig
Y Rubanova, R Shi, CF Harrigan, R Li, J Wintersinger, N Sahin, ...
Nature communications 11 (1), 731, 2020
54*2020
Neural ordinary differential equations (2018)
RTQ Chen, Y Rubanova, J Bettencourt, D Duvenaud
arXiv preprint arXiv:1806.07366, 1806
511806
Portraits of genetic intra-tumour heterogeneity and subclonal selection across cancer types
SC Dentro, I Leshchiner, K Haase, M Tarabichi, J Wintersinger, ...
BioRxiv, 312041, 2018
50*2018
Amortized bayesian optimization over discrete spaces
Y Rubanova, D Dohan, K Swersky, K Murphy
Conference on Uncertainty in Artificial Intelligence, 769-778, 2020
41*2020
Graph network simulators can learn discontinuous, rigid contact dynamics
KR Allen, TL Guevara, Y Rubanova, K Stachenfeld, A Sanchez-Gonzalez, ...
Conference on Robot Learning, 1157-1167, 2023
302023
Constraint-based graph network simulator
Y Rubanova, A Sanchez-Gonzalez, T Pfaff, P Battaglia
arXiv preprint arXiv:2112.09161, 2021
262021
Learning rigid dynamics with face interaction graph networks
KR Allen, Y Rubanova, T Lopez-Guevara, W Whitney, ...
arXiv preprint arXiv:2212.03574, 2022
252022
Very deep graph neural networks via noise regularisation
J Godwin, M Schaarschmidt, A Gaunt, A Sanchez-Gonzalez, Y Rubanova, ...
arXiv preprint arXiv:2106.07971 2, 2021
242021
TrackSigFreq: subclonal reconstructions based on mutation signatures and allele frequencies
CF Harrigan, Y Rubanova, Q Morris, A Selega
PACIFIC SYMPOSIUM ON BIOCOMPUTING 2020, 238-249, 2019
132019
Portraits of genetic intra-tumour heterogeneity and subclonal selection across cancer types. bioRxiv (2018)
SC Dentro, I Leshchiner, K Haase, M Tarabichi, J Wintersinger, ...
URL https://www. biorxiv. org/content/10.1101/312041v4, 0
4
Author Correction: Comprehensive analysis of chromothripsis in 2,658 human cancers using whole-genome sequencing
I Cortés-Ciriano, JJK Lee, R Xi, D Jain, YL Jung, L Yang, D Gordenin, ...
nature genetics 55 (6), 1076-1076, 2023
22023
Author Correction: The evolutionary history of 2,658 cancers
M Gerstung, C Jolly, I Leshchiner, SC Dentro, S Gonzalez, D Rosebrock, ...
Nature 614 (7948), E42-E42, 2023
22023
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