Items where Author is "Nemeth, Christopher"

Journal Article

Aicher, Christopher and Putcha, Srshti and Nemeth, Christopher and Fearnhead, Paul and Fox, Emily B. (2025) Stochastic Gradient MCMC for Nonlinear State Space Models*. Bayesian Analysis, 20 (1). pp. 1385-1407. ISSN 1936-0975

Gong, Mengyi and Killick, Rebecca and Nemeth, Christopher and Quinton, John (2025) A changepoint approach to modelling non-stationary soil moisture dynamics. Journal of the Royal Statistical Society. Series C: Applied Statistics: qlaf004. ISSN 0035-9254

Papamarkou, Theodore and Skoularidou, Maria and Palla, Konstantina and Aitchison, Laurence and Arbel, Julyan and Dunson, David and Filippone, Maurizio and Fortuin, Vincent and Hennig, Philipp and Hernández-Lobato, José Miguel and Hubin, Aliaksandr and Immer, Alexander and Karaletsos, Theofanis and Khan, Mohammad Emtiyaz and Kristiadi, Agustinus and Li, Yingzhen and Mandt, Stephan and Nemeth, Christopher and Osborne, Michael A. and Rudner, Tim G. J. and Rügamer, David and Teh, Yee Whye and Welling, Max and Wilson, Andrew Gordon and Zhang, Ruqi (2024) Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI. Proceedings of Machine Learning Research, 235. pp. 39556-39586. ISSN 1938-7228

Turnbull, Kathryn and Lunagomez, Simon and Nemeth, Christopher and Airoldi, Edoardo (2024) Latent Space Modelling of Hypergraph Data. Journal of the American Statistical Association, 119 (548). pp. 2634-2646. ISSN 0162-1459

Cabezas Gonzalez, Alberto and Sharrock, Louis and Nemeth, Christopher (2024) Markovian Flow Matching : Accelerating MCMC with Continuous Normalizing Flows. Advances in Neural Information Processing Systems. ISSN 1049-5258 (In Press)

Sharrock, Louis and Dodd, Daniel and Nemeth, Christopher (2024) Tuning-Free Maximum Likelihood Training of Latent Variable Models via Coin Betting. Proceedings of Machine Learning Research, 238. pp. 1810-1818. ISSN 1938-7228

Cabezas, Alberto and Battiston, Marco and Nemeth, Christopher (2024) Robust Bayesian nonparametric variable selection for linear regression. Stat, 13 (2): e696. ISSN 2049-1573

Dodd, Daniel and Sharrock, Louis and Nemeth, Christopher (2024) Learning-Rate-Free Stochastic Optimization over Riemannian Manifolds. Proceedings of Machine Learning Research. ISSN 1938-7228 (In Press)

Nemeth, Christopher (2024) Seconder of the vote of thanks and contribution to the Discussion of ‘the Discussion Meeting on Probabilistic and statistical aspects of machine learning’. Journal of the Royal Statistical Society: Series B (Statistical Methodology). ISSN 1369-7412

Shu, Qingying and Killick, Rebecca and Leeson, Amber and Nemeth, Christopher and Fettweis, Xavier and Hogg, A and Leslie, David (2023) Characterising the ice sheet surface in North East Greenland using Sentinel-1 SAR data. Journal of Glaciology, 69 (278). pp. 1834-1845. ISSN 0022-1430

Vyner, Callum and Nemeth, Christopher and Sherlock, Chris (2023) SwISS : A Scalable Markov chain Monte Carlo Divide-and-Conquer Strategy. Stat, 12 (1): e523. ISSN 2049-1573

Sharrock, Louis and Mackey, Lester and Nemeth, Christopher (2023) Learning Rate Free Sampling in Constrained Domains. Advances in Neural Information Processing Systems, 36. ISSN 1049-5258

Sharrock, Louis and Mackey, Lester and Nemeth, Christopher (2023) Learning Rate Free Bayesian Inference in Constrained Domains. Advances in Neural Information Processing Systems, 37. ISSN 1049-5258 (In Press)

Sharrock, Louis and Nemeth, Christopher (2023) Coin Sampling : Gradient-Based Bayesian Inference without Learning Rates. Proceedings of Machine Learning Research, 202. pp. 30850-30882. ISSN 1938-7228

Coullon, Jeremie and South, Leah and Nemeth, Christopher (2023) Efficient and generalizable tuning strategies for stochastic gradient MCMC. Statistics and Computing, 33 (3): 66. ISSN 0960-3174

Putcha, Srshti and Nemeth, Christopher and Fearnhead, Paul (2023) Preferential Subsampling for Stochastic Gradient Langevin Dynamics. Proceedings of Machine Learning Research, 206. pp. 8837-8856. ISSN 2640-3498

Cabezas, Alberto and Nemeth, Christopher (2023) Transport Elliptical Slice Sampling. Proceedings of Machine Learning Research, 206. pp. 3664-3676. ISSN 2640-3498

Turnbull, Kathryn and Nemeth, Christopher and Nunes, Matthew and McCormick, Tyler (2023) Sequential Estimation of Temporally Evolving Latent Space Network Models. Computational Statistics and Data Analysis, 179: 107627. ISSN 0167-9473

South, Leah and Karvonen, Toni and Nemeth, Christopher and Girolami, Mark and Oates, Chris J. (2022) Semi-Exact Control Functionals From Sard's Method. Biometrika, 109 (2). pp. 351-367. ISSN 0006-3444

Fairbrother, Jamie and Nemeth, Christopher and Pinder, Thomas and Rischard, Maxime and Brea, Johanni (2022) GaussianProcesses.jl: A Nonparametric Bayes package for the Julia Language. Journal of Statistical Software, 102 (1). pp. 1-36. ISSN 1548-7660

Coullon, Jeremie and Nemeth, Christopher (2022) SGMCMCJax : a lightweight JAX library for stochastic gradient Markov chain Monte Carlo algorithms. Journal of Open Source Software, 7 (72): 4113. ISSN 2475-9066

Pinder, Thomas and Hollaway, Michael and Nemeth, Christopher and Young, Paul J. and Leslie, David (2021) A Probabilistic Assessment of the COVID-19 Lockdown on Air Quality in the UK. arxiv.org.

Nemeth, Christopher and Fearnhead, Paul (2021) Stochastic gradient Markov chain Monte Carlo. Journal of the American Statistical Association, 1116 (533). pp. 433-450. ISSN 0162-1459

Pinder, Thomas and Nemeth, Christopher and Leslie, David (2020) Stein Variational Gaussian Processes. arXiv.

Verjans, Vincent and Leeson, Amber and Nemeth, Christopher and Stevens, C. Max and Munneke, Peter Kuipers and Noël, Brice and Wessem, Jan Melchior van (2020) Bayesian calibration of firn densification models. Cryosphere, 14. pp. 3017-3032. ISSN 1994-0416

Turnbull, Kathryn and Lunagomez Coria, Simon and Nemeth, Christopher and Airoldi, Edoardo (2019) Latent Space Representations of Hypergraphs. arxiv.org.

Baker, Jack and Fearnhead, Paul and Fox, Emily B. and Nemeth, Christopher (2019) Control variates for stochastic gradient MCMC. Statistics and Computing, 29 (3). pp. 599-615. ISSN 0960-3174

Aicher, Christopher and Putcha, Srshti and Nemeth, Christopher and Fearnhead, Paul and Fox, Emily B. (2019) Stochastic Gradient MCMC for Nonlinear State Space Models. arXiv.

Nemeth, Christopher and Sherlock, Christopher Gerrard (2018) Merging MCMC subposteriors through Gaussian-Process Approximations. Bayesian Analysis, 13 (2). pp. 507-530. ISSN 1936-0975

Nemeth, Christopher and Fearnhead, Paul and Mihaylova, Lyudmila Stoyanova (2016) Particle approximations of the score and observed information matrix for parameter estimation in state space models with linear computational cost. Journal of Computational and Graphical Statistics, 25 (4). pp. 1138-1157. ISSN 1061-8600

Nemeth, Christopher and Sherlock, Christopher and Fearnhead, Paul (2016) Particle Metropolis-adjusted Langevin algorithms. Biometrika, 103 (3). pp. 701-717. ISSN 0006-3444

Nemeth, Christopher and Fearnhead, Paul and Mihaylova, Lyudmila (2014) Sequential Monte Carlo methods for state and parameter estimation in abruptly changing environments. IEEE Transactions on Signal Processing, 62 (5). pp. 1245-1255. ISSN 1053-587X

Nemeth, Christopher and Fearnhead, Paul (2014) Particle Metropolis adjusted Langevin algorithms for state space models. arxiv.org. (Unpublished)

Contribution in Book/Report/Proceedings

Nemeth, Christopher and Fearnhead, Paul and Mihaylova, Lyudmila and Vorley, D. (2012) Bearings-Only Tracking with Particle Filtering for Joint Parameter Learning and State Estimation. In: Information Fusion (FUSION), 2012 15th International Conference on :. IEEE, SGP, pp. 824-831. ISBN 9781467304177

Nemeth, Christopher and Fearnhead, Paul and Mihaylova, Lyudmila and Vorley, D. (2012) Particle Learning Methods for State and Parameter Estimation. In: Data Fusion & Target Tracking Conference (DF&TT 2012): Algorithms & Applications, 9th IET :. UNSPECIFIED, GBR. ISBN 978-1-84919-624-6

Monograph

Sharrock, Louis and Dodd, Daniel and Nemeth, Christopher (2023) CoinEM : Tuning-Free Particle-Based Variational Inference for Latent Variable Models. Other. UNSPECIFIED.

Sharrock, Louis and Mackey, Lester and Nemeth, Christopher (2023) Learning Rate Free Bayesian Inference in Constrained Domains. Other. UNSPECIFIED.

Vyner, Callum and Nemeth, Christopher and Sherlock, Chris (2022) SwISS : A Scalable Markov chain Monte Carlo Divide-and-Conquer Strategy. Other. UNSPECIFIED.

Bolt, George and Lunagómez, Simón and Nemeth, Christopher (2022) Modelling Populations of Interaction Networks via Distance Metrics. Other. UNSPECIFIED.

Bolt, George and Lunagómez, Simón and Nemeth, Christopher (2022) Distances for Comparing Multisets and Sequences. Other. Arxiv.

Oyebamiji, Oluwole and Nemeth, Christopher and Harrison, Paula and Dunford, Rob and Cojocaru, George (2022) Multivariate sensitivity analysis for a large-scale climate impact and adaptation model. Other. Arxiv.

Pinder, Thomas and Turnbull, Kathryn and Nemeth, Christopher and Leslie, David (2021) Gaussian Processes on Hypergraphs. Other. UNSPECIFIED.

Coullon, Jeremie and South, Leah and Nemeth, Christopher (2021) Efficient and Generalizable Tuning Strategies for Stochastic Gradient MCMC. Other. Arxiv.

Cabezas, Alberto and Battiston, Marco and Nemeth, Christopher (2021) Robust Bayesian Nonparametric Variable Selection for Linear Regression. Other. UNSPECIFIED.

Contribution to Conference

Nemeth, Christopher and Lindsten, Fredrik and Filippone, Maurizio and Hensman, James (2019) Pseudo-extended Markov chain Monte Carlo. In: Thirty-third Conference on Neural Information Processing Systems, 2019-12-08 - 2019-12-14, Vancouver Convention Center.

Baker, Jack and Fearnhead, Paul and Fox, Emily B and Nemeth, Christopher (2018) Large-Scale Stochastic Sampling from the Probability Simplex. In: 32nd Neural Information Processing Systems Conference (NIPS 2018), 2018-12-03 - 2018-12-08, Palais des Congrès de Montréal.

Thesis

Cabezas Gonzalez, Alberto and Nemeth, Christopher and Battiston, Marco (2025) Advances in Bayesian Computation: Bridging Modern Machine Learning and Traditional Monte Carlo Methods. PhD thesis, Lancaster University.

Putcha, Srshti and Fearnhead, Paul and Nemeth, Christopher (2024) Scalable Bayesian Inference Using Stochastic Gradient Markov Chain Monte Carlo. PhD thesis, Lancaster University.

Duncan, Rachael and Young, Paul and Nemeth, Christopher (2024) Methods for missing time-series data and large spatial data. PhD thesis, Lancaster University.

Bolt, George and Nemeth, Christopher (2023) Statistical Methods for Samples of Interaction Networks. PhD thesis, Lancaster University.

Vyner, Callum and Sherlock, Chris and Nemeth, Christopher (2023) Contributions to Divide-and-Conquer MCMC. PhD thesis, Lancaster University.

Pinder, Thomas and Leslie, David and Nemeth, Christopher and Young, Paul (2023) Developments in Gaussian processes with applications to climate science and network problems. PhD thesis, Lancaster University.

Turnbull, Kathryn and Nemeth, Christopher and Lunagomez Coria, Simon and Nunes, Matthew (2020) Advancements in latent space network modelling. PhD thesis, Lancaster University.

Baker, Jack and Fearnhead, Paul and Nemeth, Christopher and Fox, Emily B (2019) Large-scale Bayesian computation using Stochastic Gradient Markov Chain Monte Carlo. PhD thesis, Lancaster University.

Nemeth, Christopher and Fearnhead, Paul (2014) Parameter estimation for state space models using sequential Monte Carlo algorithms. PhD thesis, Lancaster University.

Other

Bolt, George and Muncey, Harriet and Lunagomez Coria, Simon and Nemeth, Christopher (2020) Telling the Researcher STOR-i With Data Science : Elsevier data scientists are working with Lancaster University researchers to advance our understanding of researcher behaviors. UNSPECIFIED.