Publications

Theodore Papamarkou, Alexey Lindo (2024). Probability-generating function kernels for spherical data. In International Conference on Artificial Neural Networks (ICANN).

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Mustafa Hajij, Mathilde Papillon, Florian Frantzen, Jens Agerberg, Ibrahem AlJabea, Rubén Ballester, Claudio Battiloro, Guillermo Bernárdez, Tolga Birdal, Aiden Brent, Peter Chin, Sergio Escalera, Simone Fiorellino, Odin Hoff Gardaa, Gurusankar Gopalakrishnan, Devendra Govil, Josef Hoppe, Maneel Reddy Karri, Jude Khouja, Manuel Lecha, Neal Livesay, Jan Meißner, Soham Mukherjee, Alexander Nikitin, Theodore Papamarkou, Jaro Prílepok, Karthikeyan Natesan Ramamurthy, Paul Rosen, Aldo Guzmán-Sáenz, Alessandro Salatiello, Shreyas N. Samaga, Simone Scardapane, Michael T. Schaub, Luca Scofano, Indro Spinelli, Lev Telyatnikov, Quang Truong, Robin Walters, Maosheng Yang, Olga Zaghen, Ghada Zamzmi, Ali Zia, Nina Miolane (2024). TopoX: a suite of Python packages for machine learning on topological domains. In Journal of Machine Learning Research.

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Farzana Nasrin, Theodore Papamarkou, Austin Lawson, Na Gong, Orlando Rios, Vasileios Maroulas (2024). Bayesian random persistence diagram generation: an application to material microstructure analysis. In Foundations of Data Science.

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Danny Wood, Theodore Papamarkou, Matt Benatan, Richard Allmendinger (2024). Model-agnostic variable importance for predictive uncertainty: an entropy-based approach. In Data Mining and Knowledge Discovery.

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Theodore Papamarkou, Tolga Birdal, Michael M. Bronstein, Gunnar E. Carlsson, Justin Curry, Yue Gao, Mustafa Hajij, Roland Kwitt, Pietro Lio, Paolo Di Lorenzo, Vasileios Maroulas, Nina Miolane, Farzana Nasrin, Karthikeyan Natesan Ramamurthy, Bastian Rieck, Simone Scardapane, Michael T Schaub, Petar Veličković, Bei Wang, Yusu Wang, Guowei Wei, Ghada Zamzmi (2024). Position: topological deep learning is the new frontier for relational learning. In International Conference on Machine Learning (ICML).

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Theodore Papamarkou, Maria Skoularidou, Konstantina Palla, Laurence Aitchison, Julyan Arbel, David Dunson, Maurizio Filippone, Vincent Fortuin, Philipp Hennig, José Miguel Hernández-Lobato, Aliaksandr Hubin, Alexander Immer, Theofanis Karaletsos, Mohammad Emtiyaz Khan, Agustinus Kristiadi, Yingzhen Li, Stephan Mandt, Christopher Nemeth, Michael a Osborne, Tim G. J. Rudner, David Rügamer, Yee Whye Teh, Max Welling, Andrew Gordon Wilson, Ruqi Zhang (2024). Position: Bayesian deep learning is needed in the age of large-scale AI. In International Conference on Machine Learning (ICML).

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Emanuel Sommer, Lisa Wimmer, Theodore Papamarkou, Ludwig Bothmann, Bernd Bischl, David Rügamer (2024). Connecting the dots: is mode-connectedness the key to feasible sample-based inference in Bayesian neural networks?. In International Conference on Machine Learning (ICML).

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Deborshee Sen, Theodore Papamarkou, David Dunson (2024). Bayesian neural networks and dimensionality reduction. In Chapman & Hall/CRC Press.

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Mustafa Hajij, Ghada Zamzmi, Theodore Papamarkou, Aldo Guzman-Saenz, Tolga Birdal, Michael T. Schaub (2023). Combinatorial complexes: bridging the gap between cell complexes and hypergraphs. In 57th Asilomar Conference on Signals, Systems, and Computers.

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Jonas Gregor Wiese, Lisa Wimmer, Theodore Papamarkou, Bernd Bischl, Stephan Günnemann, David Rügamer (2023). Towards efficient MCMC sampling in Bayesian neural networks by exploiting symmetry. In Joint European Conference on Machine Learning and Knowledge Discovery in Databases (ECML PKDD), Research Track.

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Theodore Papamarkou (2023). Approximate blocked Gibbs sampling for Bayesian neural networks. In Statistics and Computing.

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Borja Martínez, Richard Allmendinger, Hadi Akbarzadeh Khorshidi, Theodore Papamarkou, Andre Feitas, Johanne Trippas, Markos Zachariadis, Nicholas Lord, Katie Benson (2023). Mapping the state of the art: artificial intelligence for decision making in financial crime. In Taylor & Francis/CRC Press.

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Jeremy Watts, Elexis Allen, Ahmad Mitoubsi, Anahita Khojandi, James Eales, Theodore Papamarkou (2023). Towards faster gene expression prediction via dimensionality reduction and feature selection. In 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

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Sayar Karmakar, Anirbit Mukherjee, Theodore Papamarkou (2023). Depth-2 neural networks under a data-poisoning attack. In Neurocomputing.

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Theodore Papamarkou, Farzana Nasrin, Austin Lawson, Na Gong, Orlando Rios, Vasileios Maroulas (2022). A random persistence diagram generator. In Statistics and Computing.

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Theodore Papamarkou, Jacob Hinkle, M. Todd Young, David Womble (2022). Challenges in Markov chain Monte Carlo for Bayesian neural networks. In Statistical Science.

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Jeremy Watts, Elexis Allen, Ahmad Mitoubsi, Anahita Khojandi, James Eales, Farideh Jalali-Najafabadi, Theodore Papamarkou (2022). Adapting random forests to predict obesity-associated gene expression. In 44th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

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Adam Spannaus, Theodore Papamarkou, Samantha Erwin, J. Blair Christian (2022). Inferring the spread of COVID-19: the role of time-varying reporting rate in epidemiological modelling. In Scientific Reports.

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Matt Baucum, Anahita Khojandi, Theodore Papamarkou (2021). Hidden Markov models as recurrent neural networks: an application to Alzheimer's disease. In IEEE 21th International Conference on Bioinformatics and Bioengineering (BIBE).

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Mathieu Besançon, Theodore Papamarkou, David Anthoff, Alex Arslan, Simon Byrne, Dahua Lin, John Pearson (2021). Distributions.jl: definition and modeling of probability distributions in the JuliaStats ecosystem. In Journal of Statistical Software.

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Theodore Papamarkou, Alexey Lindo, Eric B. Ford (2021). Geometric adaptive Monte Carlo in random environment. In Foundations of Data Science.

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Theodore Papamarkou, Hayley Guy, Bryce Kroencke, Jordan Miller, Preston Robinette, Daniel Schultz, Jacob Hinkle, Laura Pullum, Catherine Schuman, Jeremy Renshaw, Stylianos Chatzidakis (2021). Automated detection of corrosion in used nuclear fuel dry storage canisters using residual neural networks. In Nuclear Engineering and Technology.

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Devanshu Agrawal, Theodore Papamarkou, Jacob Hinkle (2020). Wide neural networks with bottlenecks are deep Gaussian processes. In Journal of Machine Learning Research.

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Noah W. Tuchow, Eric B. Ford, Theodore Papamarkou, Alexey Lindo (2019). The efficiency of geometric samplers for exoplanet transit timing variation models. In Monthly Notices of the Royal Astronomical Society.

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Alan Lazarus, Dirk Husmeier, Theodore Papamarkou (2018). Multiphase MCMC sampling for parameter inference in nonlinear ordinary differential equations. In International Conference on Artificial Intelligence and Statistics (AISTATS).

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Emoke-Agnes Horvat, Theodore Papamarkou (2017). Gender differences in equity crowdfunding. In Proceedings of the 5th AAAI Conference on Human Computation and Crowdsourcing (HCOMP).

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Branka Radic-Sarikas, Melinda Halasz, Kilian v. M. Huber, Georg E. Winter, Kalliopi P. Tsafou, Theodore Papamarkou, Søren Brunak, Walter Kolch, Giulio Superti-Furga (2017). Lapatinib potentiates cytotoxicity of YM155 in neuroblastoma via inhibition of the ABCB1 efflux transporter. In Scientific Reports.

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Anthony J. Lawrance, Theodore Papamarkou, Atsushi Uchida (2017). Synchronized laser chaos communication: statistical investigation of an experimental system. In IEEE Journal of Quantum Electronics.

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Branka Radic-Sarikas, Kalliopi P. Tsafou, Kristina B. Emdal, Theodore Papamarkou, Kilian v. M. Huber, Cornelia Mutz, Jeffrey A. Toretsky, Keiryn L. Bennett, Jesper v. Olsen, Søren Brunak, Heinrich Kovar, Giulio Superti-Furga (2017). Combinatorial drug screening identifies Ewing sarcoma-specific sensitivities. In Molecular Cancer Therapeutics.

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Chris J. Oates, Theodore Papamarkou, Mark Girolami (2016). The controlled thermodynamic integral for Bayesian model evidence evaluation. In Journal of the American Statistical Association.

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Dewi Harjanto, Theodore Papamarkou, Chris J. Oates, Violeta Rayon-Estrada, F. Nina Papavasiliou, Anastasia Papavasiliou (2016). RNA editing generates cellular subsets with diverse sequence within populations. In Nature Communications.

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Heinrich Kovar, James Amatruda, Erika Brunet, Stefan Burdach, Florencia Cidre-Aranaz, Enrique De Alava, Uta Dirksen, Wietske Van Der Ent, Patrick Grohar, Thomas G. P. Grünewald, Lee Helman, Peter Houghton, Kristiina Iljin, Eberhard Korsching, Marc Ladanyi, Elizabeth Lawlor, Stephen Lessnick, Joseph Ludwig, Paul Meltzer, Markus Metzler, Jaume Mora, Richard Moriggl, Takuro Nakamura, Theodore Papamarkou, Branka Radic-Sarikas, Francoise Rédini, Guenther H. S. Richter, Claudia Rossig, Keri Schadler, Beat W. Schäfer, Katia Scotlandi, Nathan C. Sheffield, Anang Shelat, Ewa Snaar-Jagalska, Poul Sorensen, Kimberly Stegmaier, Elizabeth Stewart, Alejandro Sweet-Cordero, Karoly Szuhai, Oscar M. Tirado, Franck Tirode, Jeffrey Toretsky, Kalliopi Tsafou, Aykut Üren, Andrei Zinovyev, Olivier Delattre (2016). The second European interdisciplinary Ewing sarcoma research summit – A joint effort to deconstructing the multiple layers of a complex disease. In Oncotarget.

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Raphaela Schwentner, Theodore Papamarkou, Maximilian O. Kauer, Vassilios Stathopoulos, Fan Yang, Sven Bilke, Paul S. Meltzer, Mark Girolami, Heinrich Kovar (2015). EWS-FLI1 employs an E2F switch to drive target gene expression. In Nucleic Acids Research.

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Theodore Papamarkou, Antonietta Mira, Mark Girolami (2015). Monte Carlo methods and zero variance principle. In Chapman & Hall/CRC Press.

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Theodore Papamarkou, Anthony J. Lawrance (2014). Nonlinear dynamics of trajectories generated by fully-stretching piecewise linear maps. In International Journal of Bifurcation and Chaos.

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Theodore Papamarkou, Antonietta Mira, Mark Girolami (2014). Zero variance differential geometric Markov chain Monte Carlo algorithms. In Bayesian Analysis.

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Fiona Achcar, Abeer Fadda, Jurgen R. Haanstra, Eduard J. Kerkhoven, Dong-Hyun Kim, Alejandro E. Leroux, Theodore Papamarkou, Federico Rojas, Barbara M. Bakker, Michael P. Barrett, Christine Clayton, Mark Girolami, R. Luise Krauth-Siegel, Keith R. Matthews, Rainer Breitling (2014). The silicon trypanosome: a test case of iterative model extension in systems biology. In Academic Press.

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Global Lipids Genetics Consortium (2013). Discovery and refinement of loci associated with lipid levels. In Nature Genetics.

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Global Lipids Genetics Consortium (2013). Common variants associated with plasma triglycerides and risk for coronary artery disease. In Nature Genetics.

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Theodore Papamarkou, Anthony J. Lawrance (2013). Paired Bernoulli circular spreading: attaining the BER lower bound in a CSK setting. In Circuits, Systems, and Signal Processing.

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Elizabeth H. Young, Theodore Papamarkou, Nicholas W. J. Wainwright, Manjinder S. Sandhu (2012). Genetic determinants of lipid homeostasis. In Best Practice and Research Clinical Endocrinology and Metabolism.

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ENGAGE Consortium (2011). A genome-wide screen for interactions reveals a new locus on 4p15 modifying the effect of waist-to-hip ratio on total cholesterol. In PLOS Genetics.

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Delilah Zabaneh, Meena Kumari, Manj Sandhu, Nick Wareham, Nick Wainwright, Theodore Papamarkou, Jemma Hopewell, Robert Clarke, KaWah Li, Jutta Palmen, Philippa J. Talmud, Florian Kronenberg, Claudia Lamina, Monika Summerer, Bernhard Paulweber, Jackie Price, Gerry Fowkes, Marlene Stewart, Fotios Drenos, Sonia Shah, Tina Shah, Juan-Pablo Casas, Mika Kivimaki, John Whittaker, Aroon D. Hingorani, Steve E. Humphries (2011). Meta analysis of candidate gene variants outside the LPA locus with Lp(a) plasma levels in 14,500 participants of six White European cohorts. In Atherosclerosis.

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Theodore Papamarkou (2010). Two aspects of optimum CSK communication: spreading and decoding. In World Scientific.

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Theodore Papamarkou, Anthony J. Lawrance (2007). Optimal spreading sequences for chaos-based communication systems. In International Symposium on Nonlinear Theory and its Applications (NOLTA).

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Anthony J. Lawrance, Theodore Papamarkou (2006). Higher order dependency of chaotic maps. In International Symposium on Nonlinear Theory and its Applications (NOLTA).

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