## Research groups

## Publications

### 2023

- Deveney, T., Mueller, E., & Shardlow, T. (2023) Deep surrogate accelerated delayed-acceptance HMC for Bayesian inference of spatio-temporal heat fluxes in rotating disc systems.
*SIAM Uncertainty Quantification*, DOI: 10.1137/22M1513113.## bib

@article{teo_hmc, author = {Deveney, T. and Mueller, E. and Shardlow, T.}, title = {Deep surrogate accelerated delayed-acceptance HMC for Bayesian inference of spatio-temporal heat fluxes in rotating disc systems}, eprinttype = {arxiv}, eprint = {2204.02272}, journal = {SIAM Uncertainty Quantification}, doi = {10.1137/22M1513113}, year = {2023}, vol = {11}, number = {3} }

- Delos Reyes, J., Shardlow, T., elgado-Charro, M.B., Webb, S., & White, K.A.J. (2023) Mathematical Modelling of Droplet Evaporation and Surfactant Effects on Pesticide Leaf Uptake.
## bib

@online{delosreyes2023, author = {{Delos Reyes}, J. and Shardlow, T. and elgado-Charro, M. B. and Webb, S. and White, K. A. J.}, title = {Mathematical Modelling of Droplet Evaporation and Surfactant Effects on Pesticide Leaf Uptake}, year = {2023}, eprinttype = {SSRN}, eprint = {4331165}, url = {https://ssrn.com/abstract=4331165} }

### 2022

- Tang, H., Deveney, T., Shardlow, T., & Lock, G. (2022) Use of Bayesian Statistics to Calculate Transient Heat Fluxes on Compressor Discs.
*Physics of Fluids*, DOI: 10.1063/5.0091371.## bib

@article{tep, doi = {10.1063/5.0091371}, url = {https://doi.org/10.1063%2F5.0091371}, year = {2022}, month = apr, publisher = {{AIP} Publishing}, author = {Tang, Hui and Deveney, Teo and Shardlow, Tony and Lock, Gary}, title = {Use of Bayesian Statistics to Calculate Transient Heat Fluxes on Compressor Discs}, journal = {Physics of Fluids} }

- Cornalba, F. & Shardlow, T. (2022) The Regularised Inertial Dean-Kawasaki equation: discontinuous Galerkin approximation and modelling for low-density regime.
## bib

@eprint{2207.09989, author = {Cornalba, Federico and Shardlow, Tony}, title = {The Regularised Inertial {Dean-Kawasaki} equation: discontinuous Galerkin approximation and modelling for low-density regime}, year = {2022}, eprinttype = {arxiv}, eprint = {2207.09989}, github = {tonyshardlow/RIDK-FD} }

- Deveney, T. (2022) Accelerating Bayesian inference with physics-governed likelihoods using deep learning (PhD thesis).
## bib

@phdthesis{deveney:phd, author = {Deveney, Teo}, title = {Accelerating {Bayesian} inference with physics-governed likelihoods using deep learning}, school = {Department of Mathematical Sciences, University of Bath, co-supervised with E. Mueller}, year = {2022}, uni = {researchportal.bath.ac.uk/en/studentTheses/accelerating-bayesian-inference-with-physics-governed-likelihoods} }

- Delos Reyes, J., Shardlow, T., Delgado-Charro, M.B., Webb, S., & White, K.A.J. (2022) Mathematical modelling of adjuvant-enhanced active ingredient leaf uptake of pesticides.
## bib

@online{delosreyes2022, author = {{Delos Reyes}, J. and Shardlow, T. and Delgado-Charro, M. B. and Webb, S. and White, K. A. J.}, title = {Mathematical modelling of adjuvant-enhanced active ingredient leaf uptake of pesticides}, year = {2022}, eprinttype = {arxiv}, eprint = {2210.11205} }