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Stephan Mandt
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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
9462018
Stochastic Gradient Descent as Approximate Bayesian Inference
S Mandt, MD Hoffman, DM Blei
Journal of Machine Learning Research 18, 1-35, 2017
7242017
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
5342012
Dynamic Word Embeddings
R Bamler, S Mandt
International Conference on Machine Learning 70, 380-389, 2017
4722017
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
4142020
GP-VAE: Deep Probabilistic Time Series Imputation
V Fortuin, D Baranchuk, G Rätsch, S Mandt
Artificial Intelligence and Statistics (AISTATS), 2020, 2020
3522020
Disentangled Sequential Autoencoder
Y Li, S Mandt
International Conference on Machine Learning 80, 5670-5679, 2018
3462018
Image anomaly detection with generative adversarial networks
L Deecke, R Vandermeulen, L Ruff, S Mandt, M Kloft
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2019
2932019
Diffusion probabilistic modeling for video generation
R Yang, P Srivastava, S Mandt
Entropy 25 (10), 1469, 2023
2422023
Iterative Amortized Inference
J Marino, Y Yue, S Mandt
International Conference on Machine Learning 80, 3403--3412, 2018
1982018
A Variational Analysis of Stochastic Gradient Algorithms
S Mandt, MD Hoffman, DM Blei
International Conference on Machine Learning 48, 354--363, 2016
1852016
Exponential Family Embeddings
MR Rudolph, FJR Ruiz, S Mandt, DM Blei
Neural Information Processing Systems, 2016
1602016
Neural Transformation Learning for Deep Anomaly Detection Beyond Images
C Qiu, T Pfrommer, M Kloft, S Mandt, M Rudolph
International Conference on Machine Learning, 2021
1562021
Improving inference for neural image compression
Y Yang, R Bamler, S Mandt
Neural Information Processing Systems, 2020
1322020
An introduction to neural data compression
Y Yang, S Mandt, L Theis
Foundations and Trends® in Computer Graphics and Vision 15 (2), 113-200, 2023
1212023
Equilibration rates and negative absolute temperatures for ultracold atoms in optical lattices
A Rapp, S Mandt, A Rosch
Phys. Rev. Lett. 105 (220405), 2010
1122010
Deep Generative Video Compression
J Han, S Lombardo, C Schroers, S Mandt
Neural Information Processing Systems, 2019
105*2019
Lossy image compression with conditional diffusion models
R Yang, S Mandt
Thirty-seventh Conference on Neural Information Processing Systems, 2023
1022023
Determinantal Point Processes for Mini-Batch Diversification
C Zhang, H Kjellström, S Mandt
Uncertainty in Artificial Intelligence, 2017
962017
Machine learning in thermodynamics: Prediction of activity coefficients by matrix completion
F Jirasek, RAS Alves, J Damay, RA Vandermeulen, R Bamler, M Bortz, ...
The journal of physical chemistry letters 11 (3), 981-985, 2020
922020
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