Brooks Paige
Brooks Paige
Research Fellow, Alan Turing Institute
Verified email at robots.ox.ac.uk - Homepage
TitleCited byYear
Grammar variational autoencoder
MJ Kusner, B Paige, JM HernŠndez-Lobato
Proceedings of the 34th International Conference on Machine Learning, 1945-1954, 2017
1502017
Learning disentangled representations with semi-supervised deep generative models
N Siddharth, B Paige, JW Van de Meent, A Desmaison, F Wood, ...
Advances in Neural Information Processing Systems (NIPS) 30, 5925–5935, 2017
105*2017
Inference networks for sequential Monte Carlo in graphical models
B Paige, F Wood
Proceedings of the 33rd International Conference on Machine Learning, 3040-3049, 2016
652016
A compilation target for probabilistic programming languages
B Paige, F Wood
Proceedings of The 31st International Conference on Machine Learning, 1935--1943, 2014
562014
Asynchronous anytime sequential monte carlo
B Paige, F Wood, A Doucet, YW Teh
Advances in Neural Information Processing Systems, 3410-3418, 2014
382014
Structured Disentangled Representations
B Esmaeili, H Wu, S Jain, A Bozkurt, N Siddharth, B Paige, DH Brooks, ...
arXiv preprint arXiv:1804.02086, 2018
34*2018
Bayesian inference and online experimental design for mapping neural microcircuits
B Shababo, B Paige, A Pakman, L Paninski
Advances in Neural Information Processing Systems, 1304-1312, 2013
192013
Black-box policy search with probabilistic programs
JW Van De Meent, B Paige, D Tolpin, F Wood
Journal of Machine Learning Research, 2016
182016
An introduction to probabilistic programming
JW van de Meent, B Paige, H Yang, F Wood
arXiv preprint arXiv:1809.10756, 2018
162018
Interacting particle Markov chain Monte Carlo
T Rainforth, C Naesseth, F Lindsten, B Paige, JW Vandemeent, A Doucet, ...
International Conference on Machine Learning, 2616-2625, 2016
142016
Learning a Generative Model for Validity in Complex Discrete Structures
D Janz, J van der Westhuizen, B Paige, MJ Kusner, ...
International Conference on Learning Representations (ICLR), 2018
92018
Inducing interpretable representations with variational autoencoders
N Siddharth, B Paige, A Desmaison, V de Meent, F Wood, ND Goodman, ...
arXiv preprint arXiv:1611.07492, 2016
82016
Tempering by subsampling
JW van de Meent, B Paige, F Wood
arXiv preprint arXiv:1401.7145, 2014
62014
Grammar Variational Autoencoder, 2017
MJ Kusner, B Paige, JM HernŠndez-Lobato
arXiv preprint arXiv:1703.01925, 0
6
Take a look around: using street view and satellite images to estimate house prices
S Law, B Paige, C Russell
arXiv preprint arXiv:1807.07155, 2018
42018
Output-sensitive adaptive Metropolis-Hastings for probabilistic programs
D Tolpin, JW van de Meent, B Paige, F Wood
Joint European Conference on Machine Learning and Knowledge Discovery in†…, 2015
42015
A Generative Model For Electron Paths
J Bradshaw, MJ Kusner, B Paige, MHS Segler, JM HernŠndez-Lobato
arXiv preprint arXiv:1805.10970, 2018
32018
Probabilistic structure discovery in time series data
D Janz, B Paige, T Rainforth, JW van de Meent, F Wood
arXiv preprint arXiv:1611.06863, 2016
32016
Super-sampling with a reservoir.
B Paige, D Sejdinovic, FD Wood
UAI, 2016
32016
A Model to Search for Synthesizable Molecules
J Bradshaw, B Paige, MJ Kusner, MHS Segler, JM HernŠndez-Lobato
arXiv preprint arXiv:1906.05221, 2019
22019
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Articles 1–20