‪José Miguel Hernández-Lobato‬

Navedeno

	Vse	Od leta 2020
Navedbe	17509	13972
indeks h	57	53
indeks i10	126	116

3300

1650

825

2475

201320142015201620172018201920202021202220232024202551 72 130 264 503 936 1425 1944 2520 2636 3044 3252 567

Javni dostop

Prikaži vse

58 člankov

0 člankov

na voljo

ni na voljo

Na podlagi zahtev v povezavi s financiranjem

Soavtorji

Richard E TurnerProfessor, University of CambridgePreverjeni e-poštni naslov na cam.ac.uk
Daniel Hernández-LobatoAssociate Professor, Universidad Autónoma de MadridPreverjeni e-poštni naslov na uam.es
Zoubin GhahramaniProfessor, University of Cambridge, and Distinguished Researcher, GooglePreverjeni e-poštni naslov na eng.cam.ac.uk
Ryan P. AdamsPrinceton UniversityPreverjeni e-poštni naslov na princeton.edu
Javier AntoranUniversity of CambridgePreverjeni e-poštni naslov na cam.ac.uk
Cheng ZhangGenAI, MetaPreverjeni e-poštni naslov na meta.com
Yingzhen LiImperial College LondonPreverjeni e-poštni naslov na imperial.ac.uk
Alan Aspuru-GuzikProfessor of Chemistry and Computer Science, University of Toronto (starting July 1, 2018)Preverjeni e-poštni naslov na utoronto.ca
Sebastian TschiatschekUniversity of ViennaPreverjeni e-poštni naslov na univie.ac.at
Brooks PaigeAssociate Professor, University College LondonPreverjeni e-poštni naslov na ucl.ac.uk
Matt J. KusnerPolytechnique Montréal, Mila - Quebec AI InstitutePreverjeni e-poštni naslov na mila.quebec
Bernhard SchölkopfDirector, Max Planck Institute for Intelligent Systems & ELLIS Institute Tübingen; Professor at ETHPreverjeni e-poštni naslov na tuebingen.mpg.de
Austin TrippValence LabsPreverjeni e-poštni naslov na valencelabs.com
Eric NalisnickAssistant Professor, Johns Hopkins UniversityPreverjeni e-poštni naslov na jhu.edu
Chao MaSenior Researcher, Microsoft Research CambridgePreverjeni e-poštni naslov na microsoft.com
Neil HoulsbyGooglePreverjeni e-poštni naslov na google.com
James Urquhart AllinghamGoogle DeepMindPreverjeni e-poštni naslov na cam.ac.uk
Thang D BuiLecturer, Australian National UniversityPreverjeni e-poštni naslov na anu.edu.au
Gregor N. C. SimmMicrosoft ResearchPreverjeni e-poštni naslov na microsoft.com
Erik DaxbergerApplePreverjeni e-poštni naslov na apple.com

Spremljaj

José Miguel Hernández-Lobato

Professor of Machine Learning, University of Cambridge

Preverjeni e-poštni naslov na cam.ac.uk - Domača stran

Bayesian deep learning approximate inference deep generative modeling automatic molecular design reinforcement learning


Naslov Razvrsti po navedbah Razvrsti po letniku Razvrsti po naslovu	Navedeno Navedeno	Leto
Automatic chemical design using a data-driven continuous representation of molecules R Gómez-Bombarelli, JN Wei, D Duvenaud, JM Hernández-Lobato, ... ACS central science 4 (2), 268-276, 2018	3738	2018
Probabilistic backpropagation for scalable learning of bayesian neural networks JM Hernández-Lobato, R Adams International conference on machine learning, 1861-1869, 2015	1214	2015
Grammar variational autoencoder MJ Kusner, B Paige, JM Hernández-Lobato International conference on machine learning, 1945-1954, 2017	1193	2017
Predictive entropy search for efficient global optimization of black-box functions JM Hernández-Lobato, MW Hoffman, Z Ghahramani Advances in neural information processing systems 27, 2014	862	2014
Minerva: Enabling low-power, highly-accurate deep neural network accelerators B Reagen, P Whatmough, R Adolf, S Rama, H Lee, SK Lee, ... ACM SIGARCH Computer Architecture News 44 (3), 267-278, 2016	778	2016
Decomposition of uncertainty in Bayesian deep learning for efficient and risk-sensitive learning S Depeweg, JM Hernandez-Lobato, F Doshi-Velez, S Udluft International conference on machine learning, 1184-1193, 2018	499	2018
Constrained Bayesian Optimization for Automatic Chemical Design RR Griffiths, JM Hernández-Lobato arXiv preprint arXiv:1709.05501, 2017	476*	2017
Gans for sequences of discrete elements with the gumbel-softmax distribution MJ Kusner, JM Hernández-Lobato arXiv preprint arXiv:1611.04051, 2016	391	2016
Black-box alpha divergence minimization J Hernandez-Lobato, Y Li, M Rowland, T Bui, D Hernández-Lobato, ... International conference on machine learning, 1511-1520, 2016	287	2016
Deep Gaussian processes for regression using approximate expectation propagation T Bui, D Hernández-Lobato, J Hernandez-Lobato, Y Li, R Turner International conference on machine learning, 1472-1481, 2016	284	2016
Predictive entropy search for multi-objective bayesian optimization D Hernández-Lobato, J Hernandez-Lobato, A Shah, R Adams International conference on machine learning, 1492-1501, 2016	283	2016
Deterministic variational inference for robust bayesian neural networks A Wu, S Nowozin, E Meeds, RE Turner, JM Hernandez-Lobato, AL Gaunt arXiv preprint arXiv:1810.03958, 2018	234	2018
Parallel and distributed Thompson sampling for large-scale accelerated exploration of chemical space JM Hernández-Lobato, J Requeima, EO Pyzer-Knapp, A Aspuru-Guzik International conference on machine learning, 1470-1479, 2017	230	2017
Learning and policy search in stochastic dynamical systems with bayesian neural networks S Depeweg, JM Hernández-Lobato, F Doshi-Velez, S Udluft arXiv preprint arXiv:1605.07127, 2016	217	2016
Probabilistic matrix factorization with non-random missing data JM Hernández-Lobato, N Houlsby, Z Ghahramani International conference on machine learning, 1512-1520, 2014	208	2014
A general framework for constrained Bayesian optimization using information-based search JM Hern, MA Gelbart, RP Adams, MW Hoffman, Z Ghahramani Journal of Machine Learning Research 17 (160), 1-53, 2016	203	2016
Sequence tutor: Conservative fine-tuning of sequence generation models with kl-control N Jaques, S Gu, D Bahdanau, JM Hernández-Lobato, RE Turner, D Eck International Conference on Machine Learning, 1645-1654, 2017	201	2017
Predictive entropy search for Bayesian optimization with unknown constraints JM Hernández-Lobato, M Gelbart, M Hoffman, R Adams, Z Ghahramani International conference on machine learning, 1699-1707, 2015	196	2015
Sample-efficient optimization in the latent space of deep generative models via weighted retraining A Tripp, E Daxberger, JM Hernández-Lobato Advances in Neural Information Processing Systems 33, 11259-11272, 2020	164	2020
Collaborative gaussian processes for preference learning N Houlsby, F Huszar, Z Ghahramani, J Hernández-lobato Advances in neural information processing systems 25, 2012	164	2012

Sistem trenutno ne more izvesti postopka. Poskusite znova pozneje.

Članki 1–20

Št. navedb na leto

Podvojene navedbe

Združene navedbe

Dodajanje soavtorjevSoavtorji

Spremljaj

Navedeno

Soavtorji