Vincent Adam
Vincent Adam
Pompeu Fabra University
Verified email at - Homepage
Cited by
Cited by
VBA: a probabilistic treatment of nonlinear models for neurobiological and behavioural data
J Daunizeau, V Adam, L Rigoux
PLoS computational biology 10 (1), e1003441, 2014
Perceptual bias reveals slow-updating in autism and fast-forgetting in dyslexia
I Lieder, V Adam, O Frenkel, S Jaffe-Dax, M Sahani, M Ahissar
Nature neuroscience 22 (2), 256-264, 2019
A framework for interdomain and multioutput Gaussian processes
M Van der Wilk, V Dutordoir, ST John, A Artemev, V Adam, J Hensman
arXiv preprint arXiv:2003.01115, 2020
Prior context in audition informs binding and shapes simple features
C Chambers, S Akram, V Adam, C Pelofi, M Sahani, S Shamma, ...
Nature communications 8 (1), 15027, 2017
Language facilitates introspection: Verbal mind-wandering has privileged access to consciousness
M Bastian, S Lerique, V Adam, MS Franklin, JW Schooler, J Sackur
Consciousness and Cognition 49, 86-97, 2017
Banded matrix operators for Gaussian Markov models in the automatic differentiation era
N Durrande, V Adam, L Bordeaux, S Eleftheriadis, J Hensman
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
Doubly sparse variational Gaussian processes
V Adam, S Eleftheriadis, A Artemev, N Durrande, J Hensman
International Conference on Artificial Intelligence and Statistics, 2874-2884, 2020
Dual parameterization of sparse variational Gaussian processes
V Adam, P Chang, MEE Khan, A Solin
Advances in Neural Information Processing Systems 34, 11474-11486, 2021
Scalable transformed additive signal decomposition by non-conjugate Gaussian process inference
V Adam, J Hensman, M Sahani
2016 IEEE 26th international workshop on machine learning for signal …, 2016
Disentangled skill embeddings for reinforcement learning
JC Petangoda, S Pascual-Diaz, V Adam, P Vrancx, J Grau-Moya
arXiv preprint arXiv:1906.09223, 2019
Sparse algorithms for Markovian Gaussian processes
W Wilkinson, A Solin, V Adam
International Conference on Artificial Intelligence and Statistics, 1747-1755, 2021
Structured variational inference for coupled gaussian processes
V Adam
arXiv preprint arXiv:1711.01131, 2017
Scalable GAM using sparse variational Gaussian processes
V Adam, N Durrande, ST John
arXiv preprint arXiv:1812.11106, 2018
Bellman: A toolbox for model-based reinforcement learning in tensorflow
J McLeod, H Stojic, V Adam, D Kim, J Grau-Moya, P Vrancx, F Leibfried
arXiv preprint arXiv:2103.14407, 2021
Non-linear regression models for behavioral and neural data analysis
V Adam, A Hyafil
arXiv preprint arXiv:2002.00920, 2020
Discrete flow posteriors for variational inference in discrete dynamical systems
L Aitchison, V Adam, SC Turaga
arXiv preprint arXiv:1805.10958, 2018
Efficient computational inference
V Adam, S Eleftheriadis, N Durrande, A Artemev, J Hensman, L Bordeaux
US Patent App. 17/753,723, 2022
Variational Gaussian Process Diffusion Processes
P Verma, V Adam, A Solin
International Conference on Artificial Intelligence and Statistics, 1909-1917, 2024
Placement Project: Sparse State inference for GPSSM and SDE latent models
V Adam, A Artemev
Probabilistic models of contextual effects in Auditory Pitch Perception
V Adam
UCL (University College London), 2018
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