Tiago Ramalho
Tiago Ramalho
Google DeepMind
Bestätigte E-Mail-Adresse bei tum.de
Titel
Zitiert von
Zitiert von
Jahr
Overcoming catastrophic forgetting in neural networks
J Kirkpatrick, R Pascanu, N Rabinowitz, J Veness, G Desjardins, AA Rusu, ...
Proceedings of the national academy of sciences 114 (13), 3521-3526, 2017
23882017
Hybrid computing using a neural network with dynamic external memory
A Graves, G Wayne, M Reynolds, T Harley, I Danihelka, ...
Nature 538 (7626), 471-476, 2016
12972016
Conditional neural processes
M Garnelo, D Rosenbaum, C Maddison, T Ramalho, D Saxton, ...
International Conference on Machine Learning, 1704-1713, 2018
2772018
The phosphorylation flow of the Vibrio harveyi quorum-sensing cascade determines levels of phenotypic heterogeneity in the population
L Plener, N Lorenz, M Reiger, T Ramalho, U Gerland, K Jung
Journal of bacteriology 197 (10), 1747-1756, 2015
482015
Adaptive posterior learning: few-shot learning with a surprise-based memory module
T Ramalho, M Garnelo
arXiv preprint arXiv:1902.02527, 2019
272019
Single cell analysis of a bacterial sender-receiver system
T Ramalho, A Meyer, A Mückl, K Kapsner, U Gerland, FC Simmel
PLoS One 11 (1), e0145829, 2016
242016
Reply to Huszár: The elastic weight consolidation penalty is empirically valid
J Kirkpatrick, R Pascanu, N Rabinowitz, J Veness, G Desjardins, AA Rusu, ...
Proceedings of the National Academy of Sciences 115 (11), E2498-E2498, 2018
122018
Simulation of stochastic network dynamics via entropic matching
T Ramalho, M Selig, U Gerland, TA Ensslin
Physical Review E 87 (2), 022719, 2013
112013
Encoding spatial relations from natural language
T Ramalho, T Kočiský, F Besse, SM Eslami, G Melis, F Viola, P Blunsom, ...
arXiv preprint arXiv:1807.01670, 2018
9*2018
An empirical study of pretrained representations for few-shot classification
T Ramalho, T Sousbie, S Peluchetti
arXiv preprint arXiv:1910.01319, 2019
52019
Density estimation in representation space to predict model uncertainty
T Ramalho, M Miranda
International Workshop on Engineering Dependable and Secure Machine Learning …, 2020
32020
Information processing in biology: A study on signaling and emergent computation
T Ramalho
Universitätsbibliothek der Ludwig-Maximilians-Universität, 2015
12015
Programmable pattern formation in cellular systems with local signaling
T Ramalho, S Kremser, H Wu, U Gerland
Communications Physics 4 (1), 1-11, 2021
2021
Neural network systems implementing conditional neural processes for efficient learning
TMSP Ramalho, D ROSENBAUM, M Garnelo, C Maddison, SM Eslami, ...
US Patent App. 16/968,336, 2021
2021
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