Research output per year
Research output per year
Personal profile
Research interests
My research spans probabilistic machine learning. I am interested in addressing questions related to uncertainty quantification and to approximate inference with big data or with high-dimensional models. My two main research projects pertain to approximate Markov chain Monte Carlo (MCMC) for Bayesian deep learning and to neural network Gaussian processes (NNGPs).
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
External positions
Adjunct Professor, University of Tennessee
12 Mar 2021 → 12 Mar 2024
Research Beacons, Institutes and Platforms
- Digital Futures
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Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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Depth-2 neural networks under a data-poisoning attack
Karmakar, S., Mukherjee, A. & Papamarkou, T., 21 Feb 2023, (E-pub ahead of print) In: Neurocomputing.Research output: Contribution to journal › Article › peer-review
Open Access -
Adapting Random Forests to Predict Obesity-Associated Gene Expression
Watts, J., Allen, E., Mitoubsi, A., Khojandi, A., Eales, J., Jalali-Najafabadi, F. & Papamarkou, T., 8 Sep 2022, p. 4407-4410. 4 p.Research output: Contribution to conference › Paper › peer-review
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A random persistence diagram generator
Papamarkou, T., Nasrin, F., Lawson, A., Gong, N., Rios, O. & Maroulas, V., 7 Oct 2022, In: Statistics and Computing. 32, 5, 88.Research output: Contribution to journal › Article › peer-review
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Bayesian neural networks and dimensionality reduction
Sen, D., Papamarkou, T. & Dunson, D., 18 Jan 2022, (Accepted/In press) Handbook of Bayesian, fiducial, and frequentist inference. Berger, J., Meng, X-L., Reid, N. & Xie, M. (eds.). Chapmann & Hall and CRCResearch output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review
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Challenges in Markov chain Monte Carlo for Bayesian neural networks
Papamarkou, T., Hinkle, J., Young, M. T. & Womble, D., Aug 2022, In: Statistical Science. 37, 3, p. 425-442 18 p., 3.Research output: Contribution to journal › Article › peer-review
Open AccessFile2 Downloads (Pure)
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Centre for Digital Trust and Society
Barrett, E., Allmendinger, R., Elliot, M., Lord, N., Cordeiro, L., Gibson, R., Papamarkou, T., Dresner, D., Buil Gil, D., Aldridge, J., Duncan, P., Banach, R., Brown, G., Dennis, L., Fisher, M., Korovin, K., Kotselidis, C., Luján, M., Mustafa, M., Olivier, P., Reger, G., Zhang, N., Hodgkinson, G., Gulati, S., Ainsworth, J., Chen, Y., Green, B., Healey, M., Uyarra, E., Zachariadis, M., Little, C., Mackey, E., Nenadic, G., Keane, J., Shlomo, N., Laskowski, N., Jarwar, M. A., Shariati Samani, S., Smith, D., Kambites, M., Thorpe, M., Rowley, P., Flynn, S., Turner, P., Wainwright, V., Czerwinsky, A., Nini, A., Broad, R., Shute, J., Deakin, J., Taboada, P., Knight, P., Hutchings, S., Whyte, J., Tolz-Zilitinkevic, V., Pilkington, H., Guharoy, S., Nicolo, A., Reggiani, C., Garcia Oliva, J., Van Someren, A., Bon, E., Cantijoch Cunill, M., Koch, D. & Chen, Y.
11/05/21 → …
Project: Other
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FinTech and Financial Crimes: Methods, Applications, and Regulations
Allmendinger, R., Zachariadis, M., Buil Gil, D., Barrett, E., Lord, N., Freitas, A., Joshi, M. & Papamarkou, T.
4/10/21 → 30/09/22
Project: Research
Activities
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SIAM Conference on Mathematics of Data Science 2022
Theodoros Papamarkou (Chair)
28 Sep 2022 → 29 Sep 2022Activity: Participating in or organising event(s) › Participating in a conference, workshop, exhibition, performance, inquiry, course etc
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The premise of approximate MCMC in Bayesian deep learning
Theodoros Papamarkou (Speaker)
26 Sep 2022Activity: Talk or presentation › Invited talk
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The premise of approximate MCMC in Bayesian deep learning
Theodoros Papamarkou (Speaker)
8 Sep 2022Activity: Talk or presentation › Invited talk
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Journal of Statistical Software (Journal)
Theodore Papamarkou (Editor)
26 Jul 2021 → …Activity: Publication peer-review and editorial work › Editorial work
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Challenges in Markov chain Monte Carlo for Bayesian neural networks
Theodore Papamarkou (Speaker)
23 Apr 2021Activity: Talk or presentation › Invited talk