Martin Jankowiak
Martin Jankowiak
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Cited by
Pyro: Deep universal probabilistic programming
E Bingham, JP Chen, M Jankowiak, F Obermeyer, N Pradhan, ...
The Journal of Machine Learning Research 20 (1), 973-978, 2019
Jet Substructure at the Tevatron and LHC: New results, new tools, new benchmarks
A Altheimer, S Arora, L Asquith, G Brooijmans, J Butterworth, ...
Journal of Physics G: Nuclear and Particle Physics 39 (6), 063001, 2012
Boosted objects and jet substructure at the LHC. Report of BOOST2012, held at IFIC Valencia, 23rd–27th of July 2012
A Altheimer, A Arce, L Asquith, J Backus Mayes, EB Kuutmann, J Berger, ...
The European Physical Journal C 74, 1-24, 2014
Composable effects for flexible and accelerated probabilistic programming in NumPyro
D Phan, N Pradhan, M Jankowiak
arXiv preprint arXiv:1912.11554, 2019
Towards an understanding of the correlations in jet substructure: Report of BOOST2013, hosted by the University of Arizona, 12th–16th of August 2013
D Adams, A Arce, L Asquith, M Backovic, T Barillari, P Berta, D Bertolini, ...
The European Physical Journal C 75, 1-52, 2015
Analysis of 6.4 million SARS-CoV-2 genomes identifies mutations associated with fitness
F Obermeyer, M Jankowiak, N Barkas, SF Schaffner, JD Pyle, ...
Science 376 (6599), 1327-1332, 2022
Constraining -violating Higgs sectors at the LHC using gluon fusion
MJ Dolan, P Harris, M Jankowiak, M Spannowsky
Physical Review D 90 (7), 073008, 2014
LHC probes the hidden sector
J Jaeckel, M Jankowiak, M Spannowsky
Physics of the Dark Universe 2 (3), 111-117, 2013
Jet dipolarity: top tagging with color flow
A Hook, M Jankowiak, JG Wacker
Journal of High Energy Physics 2012 (4), 1-15, 2012
Jet substructure without trees
M Jankowiak, AJ Larkoski
Journal of High Energy Physics 2011 (6), 1-21, 2011
Pathwise Derivatives Beyond the Reparameterization Trick
M Jankowiak, F Obermeyer
Proceedings of the 35th International Conference on Machine Learning, PMLR …, 2018
Variational Bayesian optimal experimental design
A Foster, M Jankowiak, E Bingham, P Horsfall, YW Teh, T Rainforth, ...
Advances in Neural Information Processing Systems 32, 2019
LHC probes the 4251 hidden sector
J Jaeckel, M Jankowiak, M Spannowsky
Phys. Dark Univ 2, 111-117, 2013
Learning how to count: a high multiplicity search for the LHC
S El Hedri, A Hook, M Jankowiak, JG Wacker
Journal of High Energy Physics 2013 (8), 1-38, 2013
High-dimensional Bayesian optimization with sparse axis-aligned subspaces
D Eriksson, M Jankowiak
Uncertainty in Artificial Intelligence, 493-503, 2021
Parametric gaussian process regressors
M Jankowiak, G Pleiss, J Gardner
International Conference on Machine Learning, 4702-4712, 2020
Event extraction using distant supervision
K Reschke, M Jankowiak, M Surdeanu, CD Manning, D Jurafsky
Language Resources and Evaluation Conference (LREC), 2014
A unified stochastic gradient approach to designing bayesian-optimal experiments
A Foster, M Jankowiak, M O’Meara, YW Teh, T Rainforth
International Conference on Artificial Intelligence and Statistics, 2959-2969, 2020
Fast matrix square roots with applications to Gaussian processes and Bayesian optimization
G Pleiss, M Jankowiak, D Eriksson, A Damle, J Gardner
Advances in Neural Information Processing Systems 33, 22268-22281, 2020
Nearly supersymmetric dark atoms
SR Behbahani, M Jankowiak, T Rube, JG Wacker
Advances in High Energy Physics 2011, 1-34, 2011
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