| Dynamic word embeddings R Bamler, S Mandt International Conference on Machine Learning, 380-389, 2017 | 472 | 2017 |
| Giant generic topological Hall resistivity of MnSi under pressure R Ritz, M Halder, C Franz, A Bauer, M Wagner, R Bamler, A Rosch, ... Physical Review B—Condensed Matter and Materials Physics 87 (13), 134424, 2013 | 156 | 2013 |
| Improving inference for neural image compression Y Yang, R Bamler, S Mandt Advances in Neural Information Processing Systems 33, 573-584, 2020 | 133 | 2020 |
| Phase-space Berry phases in chiral magnets: Dzyaloshinskii-Moriya interaction and the charge of skyrmions F Freimuth, R Bamler, Y Mokrousov, A Rosch Physical Review B—Condensed Matter and Materials Physics 88 (21), 214409, 2013 | 112 | 2013 |
| 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 | 94 | 2020 |
| Hydrodynamic object recognition: when multipoles count AB Sichert, R Bamler, JL van Hemmen Physical review letters 102 (5), 058104, 2009 | 47 | 2009 |
| Perturbative black box variational inference R Bamler, C Zhang, M Opper, S Mandt Advances in Neural Information Processing Systems 30, 2017 | 43 | 2017 |
| Variational Bayesian Quantization Y Yang, R Bamler, S Mandt Proceedings of the 37 th International Conference on Machine Learning, 2020 | 37* | 2020 |
| Hybridizing physical and data-driven prediction methods for physicochemical properties F Jirasek, R Bamler, S Mandt Chemical Communications 56 (82), 12407-12410, 2020 | 30 | 2020 |
| Extreme Classification via Adversarial Softmax Approximation R Bamler, S Mandt arXiv preprint arXiv:2002.06298, 2020 | 29 | 2020 |
| Dynamic word embeddings SM Mandt, R Bamler US Patent 11,068,658, 2021 | 25 | 2021 |
| User-dependent neural sequence models for continuous-time event data A Boyd, R Bamler, S Mandt, P Smyth Advances in Neural Information Processing Systems 33, 21488-21499, 2020 | 24 | 2020 |
| Making thermodynamic models of mixtures predictive by machine learning: matrix completion of pair interactions F Jirasek, R Bamler, S Fellenz, M Bortz, M Kloft, S Mandt, H Hasse Chemical Science 13 (17), 4854-4862, 2022 | 23 | 2022 |
| On the challenges and opportunities in generative ai L Manduchi, K Pandey, R Bamler, R Cotterell, S Däubener, S Fellenz, ... arXiv preprint arXiv:2403.00025, 2024 | 18 | 2024 |
| Understanding Entropy Coding With Asymmetric Numeral Systems (ANS): a Statistician's Perspective R Bamler arXiv preprint arXiv:2201.01741, 2022 | 18 | 2022 |
| Improving Optimization for Models With Continuous Symmetry Breaking R Bamler, S Mandt International Conference on Machine Learning, 432-441, 2018 | 17 | 2018 |
| Structured black box variational inference for latent time series models R Bamler, S Mandt arXiv preprint arXiv:1707.01069, 2017 | 16 | 2017 |
| Verbalized Machine Learning: Revisiting Machine Learning with Language Models TZ Xiao, R Bamler, B Schölkopf, W Liu arXiv preprint arXiv:2406.04344, 2024 | 11 | 2024 |
| Augmenting and Tuning Knowledge Graph Embeddings R Bamler, F Salehi, S Mandt Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 172, 2019 | 11 | 2019 |
| Equilibration and approximate conservation laws: Dipole oscillations and perfect drag of ultracold atoms in a harmonic trap R Bamler, A Rosch Physical Review A 91 (6), 063604, 2015 | 10 | 2015 |
Stephan MandtAssociate Professor, University of California, IrvineVerified email at uci.edu