Follow
Yulia Rubanova
Title
Cited by
Cited by
Year
Neural ordinary differential equations
RTQ Chen, Y Rubanova, J Bettencourt, DK Duvenaud
Advances in neural information processing systems 31, 2018
24822018
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
5532020
Latent ordinary differential equations for irregularly-sampled time series
Y Rubanova, RTQ Chen, DK Duvenaud
Advances in neural information processing systems 32, 2019
4072019
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
1762018
Pan-cancer analysis of whole genomes.
S Hirano, L Yang, M Juul, CA Purdie, BP O'Neill, R Kabbe, ...
Nature 578 (DKFZ-2020-01051), 82-93, 2020
1422020
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
1212021
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
47*2018
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), 1-12, 2020
35*2020
Simple gnn regularisation for 3d molecular property prediction and beyond
J Godwin, M Schaarschmidt, AL Gaunt, A Sanchez-Gonzalez, ...
International conference on learning representations, 2021
212021
Amortized bayesian optimization over discrete spaces
Y Rubanova, D Dohan, K Swersky, K Murphy
Conference on Uncertainty in Artificial Intelligence, 769-778, 2020
18*2020
Very deep graph neural networks via noise regularisation
J Godwin, M Schaarschmidt, A Gaunt, A Sanchez-Gonzalez, Y Rubanova, ...
arXiv preprint arXiv:2106.07971, 2021
102021
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
82019
Portraits of genetic intra-tumour heterogeneity and subclonal selection across cancer types. bioRxiv. 2018
SC Dentro, I Leshchiner, K Haase, M Tarabichi, J Wintersinger, ...
Google Scholar, 312041, 0
6
Constraint-based graph network simulator
Y Rubanova, A Sanchez-Gonzalez, T Pfaff, P Battaglia
arXiv preprint arXiv:2112.09161, 2021
42021
A Generalist Neural Algorithmic Learner
B Ibarz, V Kurin, G Papamakarios, K Nikiforou, M Bennani, R Csordás, ...
arXiv preprint arXiv:2209.11142, 2022
2022
Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples
WU Meyerson, LJ Dursi, LB Wang, G Dong, WW Liang, A Weerasinghe, ...
Nature Publishing Group UK, 2020
2020
Sex differences in oncogenic mutational processes
SD Prokopec, RX Sun, F Yousif, N Schmitz, F Al-Shahrour, G Atwal, ...
Nature Publishing Group UK, 2020
2020
Continuous-time latent-variable models for time series
Y Rubanova
2020
The evolutionary history of 2,658 cancers
C Jolly, M Gerstung, I Leshchiner, SC Dentro, S Gonzalez, TJ Mitchell, ...
Cancer Research 78 (13_Supplement), 218-218, 2018
2018
Graph network simulators can learn discontinuous, rigid contact dynamics
KR Allen, TL Guevara, Y Rubanova, K Stachenfeld, A Sanchez-Gonzalez, ...
6th Annual Conference on Robot Learning, 0
The system can't perform the operation now. Try again later.
Articles 1–20