Stephan Mandt

Cited by

	All	Since 2016
Citations	2143	1840
h-index	23	21
i10-index	29	26

720

360

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540

20102011201220132014201520162017201820192020202110 14 45 57 84 83 101 148 324 529 719 10

Co-authors

Robert BamlerUC IrvineVerified email at uci.edu
David BleiProfessor of Statistics and Computer Science, Columbia UniversityVerified email at columbia.edu
Cheng ZhangMicrosoft Research, CambridgeVerified email at kth.se
Achim RoschInstitute for Theoretical Physics, University of CologneVerified email at thp.uni-koeln.de
Marius KloftTU KaiserslauternVerified email at cs.uni-kl.de
Florian WenzelGoogle Brain BerlinVerified email at google.com
Immanuel BlochMax-Planck Institute of Quantum Optics; Ludwig-Maximilians UniversityVerified email at mpq.mpg.de
Matthew D. HoffmanResearch Scientist, Google ResearchVerified email at google.com
Yingzhen LiImperial College LondonVerified email at imperial.ac.uk
Yisong YueCalifornia Institute of TechnologyVerified email at caltech.edu
Joseph MarinoCalifornia Institute of TechnologyVerified email at caltech.edu
Hedvig Kjellström (Sidenbladh)Professor at KTH Royal Institute of Technology, Lead AI Scientist at Silo AI, SwedenVerified email at kth.se
Salvator LombardoVerified email at cornell.edu
Maja RudolphBosch Center for Artificial IntelligenceVerified email at cs.columbia.edu
Sebastian NowozinPartner Researcher, Microsoft Research (Cambridge, UK)Verified email at microsoft.com
Tim SalimansGoogle Brain AmsterdamVerified email at google.com
Bastiaan S. VeelingUniversity of AmsterdamVerified email at uva.nl
Rodolphe JENATTONSenior machine learning scientist at Google Brain, BerlinVerified email at google.com
Kevin RothETH ZurichVerified email at inf.ethz.ch
Jasper SnoekGoogle BrainVerified email at google.com

Stephan Mandt

Assistant Professor, University of California, Irvine

Verified email at uci.edu - Homepage

Machine Learning Variational Inference Neural Compression Deep Learning Generative Models


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Fermionic transport and out-of-equilibrium dynamics in a homogeneous Hubbard model with ultracold atoms U Schneider, L Hackermüller, JP Ronzheimer, S Will, S Braun, T Best, ... Nature Physics 8 (3), 213-218, 2012	399	2012
Stochastic Gradient Descent as Approximate Bayesian Inference S Mandt, MD Hoffman, DM Blei Journal of Machine Learning Research 18, 1-35, 2017	297	2017
Advances in variational inference C Zhang, J Bütepage, H Kjellström, S Mandt IEEE transactions on pattern analysis and machine intelligence 41 (8), 2008-2026, 2018	203	2018
Dynamic Word Embeddings R Bamler, S Mandt International Conference on Machine Learning 70, 380-389, 2017	155	2017
Exponential family embeddings M Rudolph, F Ruiz, S Mandt, D Blei Advances in Neural Information Processing Systems 29, 478-486, 2016	100	2016
A Variational Analysis of Stochastic Gradient Algorithms S Mandt, MD Hoffman, DM Blei International Conference on Machine Learning 48, 354--363, 2016	96	2016
Equilibration rates and negative absolute temperatures for ultracold atoms in optical lattices A Rapp, S Mandt, A Rosch Physical review letters 105 (22), 220405, 2010	85	2010
Disentangled Sequential Autoencoder Y Li, S Mandt International Conference on Machine Learning 80, 5670-5679, 2018	70*	2018
Image anomaly detection with generative adversarial networks L Deecke, R Vandermeulen, L Ruff, S Mandt, M Kloft Joint european conference on machine learning and knowledge discovery in …, 2018	65	2018
Iterative Amortized Inference J Marino, Y Yue, S Mandt International Conference on Machine Learning 80, 3403--3412, 2018	65	2018
Determinantal Point Processes for Mini-Batch Diversification C Zhang, H Kjellström, S Mandt Uncertainty in Artificial Intelligence, 2017	56	2017
Disentangled sequential autoencoder L Yingzhen, S Mandt International Conference on Machine Learning, 5670-5679, 2018	33	2018
How good is the bayes posterior in deep neural networks really? F Wenzel, K Roth, BS Veeling, J Świątkowski, L Tran, S Mandt, J Snoek, ... International Conference on Machine Learning, 2020, 2020	32	2020
Quasi-Monte Carlo Variational Inference A Buchholz, F Wenzel, S Mandt International Conference on Machine Learning 80, 668-677, 2018	32	2018
Variational tempering S Mandt, J McInerney, F Abrol, R Ranganath, D Blei Artificial Intelligence and Statistics, 704-712, 2016	32	2016
Smoothed gradients for stochastic variational inference S Mandt, D Blei Advances in Neural Information Processing Systems 27, 2438-2446, 2014	32	2014
Factorized Variational Autoencoders for Modeling Audience Reactions to Movies Z Deng, R Navarathna, P Carr, S Mandt, Y Yue, I Matthews, G Mori Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017	31	2017
Interacting fermionic atoms in optical lattices diffuse symmetrically upwards and downwards in a gravitational potential S Mandt, A Rapp, A Rosch Physical review letters 106 (25), 250602, 2011	29	2011
GP-VAE: Deep Probabilistic Time Series Imputation V Fortuin, D Baranchuk, G Rätsch, S Mandt Artificial Intelligence and Statistics (AISTATS), 2020, 2020	28*	2020
Perturbative Black Box Variational Inference R Bamler, C Zhang, M Opper, S Mandt Neural Information Processing Systems (NIPS 2017), 2017	28	2017

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