Martin Jankowiak

Uber AI Labs

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Theoretical Physics, Mathematical Modeling, Machine Learning, Statistics, Particle Physics, Numerical Analysis, Computational Physics, Natural Language Processing, Statistical Data Analysis, Quantum Mechanics, Quantum Field Theory, Algorithms, Computer Science, Matlab, Scala, C++, Mathematica, Python, Scientific Computing, Physics, Data Analysis, Text Classification, Linear Algebra, Differential Equations, Research

Papers32 papers

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Fast Matrix Square Roots with Applications to Gaussian Processes and Bayesian Optimization

Geoff Pleiss,Martin Jankowiak,David Eriksson,Anil Damle,Jacob R. Gardner

NIPS 2020, (2020)

Cited by1EIBibtex

Parametric Gaussian Process Regressors

Martin Jankowiak,Geoff Pleiss,Jacob Gardner

ICML, pp.4702-4712, (2020)

Cited by5EIBibtex

Pyro: Deep Universal Probabilistic Programming

Eli Bingham, Jonathan P. Chen,Martin Jankowiak, Fritz Obermeyer, Neeraj Pradhan,Theofanis Karaletsos,Rohit Singh, Paul A. Szerlip, Paul Horsfall,Noah D. Goodman

The Journal of Machine Learning Research, no. 28 (2019)

Cited by246EIBibtex

Variational optimal experiment design: efficient automation of adaptive experiments

Adam Foster,Martin Jankowiak, Eli Bingham,Yee Whye Teh, Tom Rainforth, Noah Goodman

arXiv preprint arXiv:1903.05480, (2019)

Cited by3Bibtex

Composable Effects for Flexible and Accelerated Probabilistic Programming in NumPyro

Phan Du, Pradhan Neeraj,Jankowiak Martin

Bibtex

A Unified Stochastic Gradient Approach to Designing Bayesian-Optimal Experiments

Foster Adam,Jankowiak Martin, O'Meara Matthew,Teh Yee Whye, Rainforth Tom

AISTATS, pp.2959-2969, (2019)

EIBibtex

Functional Tensors for Probabilistic Programming

Obermeyer Fritz, Bingham Eli,Jankowiak Martin, Phan Du, Chen Jonathan P.

Bibtex

Sparse Gaussian Process Regression Beyond Variational Inference

Jankowiak Martin, Pleiss Geoff,Gardner Jacob R.

Bibtex

Variational Bayesian Optimal Experimental Design

Adam Foster,Martin Jankowiak, Eli Bingham, Paul Horsfall,Yee Whye Teh, Tom Rainforth,Noah Goodman

ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 32 (NIPS 2019), (2019): 14036-14047

Cited by3EIBibtex

Neural Likelihoods for Multi-Output Gaussian Processes

Martin Jankowiak,Jacob Gardner

arXiv: Machine Learning, (2019)

Cited by1EIBibtex

Variational Estimators for Bayesian Optimal Experimental Design

Adam Foster,Martin Jankowiak, Eli Bingham, Paul Horsfall,Yee Whye Teh, Tom Rainforth,Noah Goodman

arXiv: Machine Learning, (2019)

Cited by4EIBibtex

Tensor Variable Elimination for Plated Factor Graphs

Fritz Obermeyer, Eli Bingham,Martin Jankowiak, Justin Chiu, Neeraj Pradhan,Alexander M. Rush,Noah Goodman

arXiv: Machine Learning, (2019)

Cited by3EIBibtex

Pathwise Derivatives for Multivariate Distributions

Martin Jankowiak,Theofanis Karaletsos

international conference on artificial intelligence and statistics, (2018)

Cited by5EIBibtex

Closed Form Variational Objectives For Bayesian Neural Networks with a Single Hidden Layer

Martin Jankowiak

arXiv: Machine Learning, (2018)

EIBibtex

Pathwise Derivatives Beyond the Reparameterization Trick

Martin Jankowiak, Fritz Obermeyer

international conference on machine learning, (2018): 2240-2249

EIBibtex

Pyro: Deep universal probabilistic programming.(2018)

Eli Bingham, Jonathan P Chen,Martin Jankowiak, Fritz Obermeyer, Neeraj Pradhan, Theofanis Karaletsos, Rohit Singh, Paul Szerlip, Paul Horsfall, Noah D Goodman

arXiv preprint arXiv:1810.09538, (2018)

Cited by6Bibtex

Uncovering the Spatiotemporal Patterns of Collective Social Activity

Martin Jankowiak,Manuel Gomez-Rodriguez

SDM, (2017)

Cited by6EIBibtex

Towards an understanding of the correlations in jet substructure - Report of BOOST2013, hosted by the University of Arizona, 12th–16th of August 2013

D L Adams, Ayana Arce,L Asquith, M Backovic, T Barillari, Peter Berta, D Bertolini, A G Buckley, J M Butterworth, R C Camacho Toro,Julien Caudron, Y T Chien

EUROPEAN PHYSICAL JOURNAL C, no. 9 (2015)

Cited by2Bibtex

Boosted objects and jet substructure at the LHC. Report of BOOST2012, held at IFIC Valencia, 23rd–27th of July 2012

A Altheimer,A T H Arce,L Asquith,J Backus Mayes,E Bergeaas Kuutmann, James O Berger, David Martin Bjergaard, Lene Bryngemark,A G Buckley,J M Butterworth,Matteo Cacciari,M Campanelli

European Physical Journal C, no. 3 (2014): 2792

Cited by231Bibtex

Event Extraction Using Distant Supervision

Kevin Reschke,Martin Jankowiak,Mihai Surdeanu,Christopher D. Manning,Daniel Jurafsky

LREC, pp.4527-4531, (2014)

Cited by34EIBibtex

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Martin JankowiakBinding

Papers32 papers

Martin Jankowiak