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2020 – today
- 2024
[c7]Prakhar Verma, Vincent Adam, Arno Solin:
Variational Gaussian Process Diffusion Processes. AISTATS 2024: 1909-1917- 2023
- [i11]Prakhar Verma
, Vincent Adam, Arno Solin:
Variational Gaussian Process Diffusion Processes. CoRR abs/2306.02066 (2023) - 2021
- [c6]William J. Wilkinson, Arno Solin, Vincent Adam:
Sparse Algorithms for Markovian Gaussian Processes. AISTATS 2021: 1747-1755 - [c5]Vincent Adam, Paul E. Chang, Mohammad Emtiyaz Khan, Arno Solin:
Dual Parameterization of Sparse Variational Gaussian Processes. NeurIPS 2021: 11474-11486 - [i10]William J. Wilkinson, Arno Solin, Vincent Adam:
Sparse Algorithms for Markovian Gaussian Processes. CoRR abs/2103.10710 (2021) - [i9]John McLeod, Hrvoje Stojic, Vincent Adam, Dongho Kim, Jordi Grau-Moya, Peter Vrancx, Felix Leibfried:
Bellman: A Toolbox for Model-Based Reinforcement Learning in TensorFlow. CoRR abs/2103.14407 (2021) - [i8]Vincent Adam, Paul E. Chang, Mohammad Emtiyaz Khan, Arno Solin:
Dual Parameterization of Sparse Variational Gaussian Processes. CoRR abs/2111.03412 (2021) - 2020
- [c4]Vincent Adam, Stefanos Eleftheriadis, Artem Artemev, Nicolas Durrande, James Hensman:
Doubly Sparse Variational Gaussian Processes. AISTATS 2020: 2874-2884 - [i7]Vincent Adam, Stefanos Eleftheriadis, Nicolas Durrande, Artem Artemev, James Hensman:
Doubly Sparse Variational Gaussian Processes. CoRR abs/2001.05363 (2020) - [i6]Mark van der Wilk, Vincent Dutordoir, S. T. John, Artem Artemev, Vincent Adam, James Hensman:
A Framework for Interdomain and Multioutput Gaussian Processes. CoRR abs/2003.01115 (2020)
2010 – 2019
- 2019
- [c3]Nicolas Durrande, Vincent Adam, Lucas Bordeaux, Stefanos Eleftheriadis, James Hensman:
Banded Matrix Operators for Gaussian Markov Models in the Automatic Differentiation Era. AISTATS 2019: 2780-2789 - [i5]Nicolas Durrande, Vincent Adam, Lucas Bordeaux, Stefanos Eleftheriadis, James Hensman:
Banded Matrix Operators for Gaussian Markov Models in the Automatic Differentiation Era. CoRR abs/1902.10078 (2019) - [i4]Janith C. Petangoda, Sergio Pascual-Diaz, Vincent Adam, Peter Vrancx, Jordi Grau-Moya:
Disentangled Skill Embeddings for Reinforcement Learning. CoRR abs/1906.09223 (2019) - 2018
- [i3]Laurence Aitchison, Vincent Adam, Srinivas C. Turaga:
Discrete flow posteriors for variational inference in discrete dynamical systems. CoRR abs/1805.10958 (2018) - [i2]Vincent Adam, Nicolas Durrande, S. T. John:
Scalable GAM using sparse variational Gaussian processes. CoRR abs/1812.11106 (2018) - 2017
- [c2]Itay Lieder, Vincent Adam, Maneesh Sahani, Merav Ahissar:
Modelling the dynamics of integrating context into perception: in good and in poor readers. CogSci 2017 - [i1]Vincent Adam:
Structured Variational Inference for Coupled Gaussian Processes. CoRR abs/1711.01131 (2017) - 2016
- [c1]Vincent Adam, James Hensman, Maneesh Sahani:
Scalable transformed additive signal decomposition by non-conjugate Gaussian process inference. MLSP 2016: 1-6 - 2014
- [j1]Jean Daunizeau, Vincent Adam, Lionel Rigoux:
VBA: A Probabilistic Treatment of Nonlinear Models for Neurobiological and Behavioural Data. PLoS Comput. Biol. 10(1) (2014)
Coauthor Index
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