Christopher Nemeth

36 papers A* 7A 3C 1Journal 25
YearRankTypeTitle / Venue / Authors
2026 J jnl
Generator-based Graph Generation via Heat Diffusion.
CoRR
Anthony Stephenson, Ian Gallagher, Christopher Nemeth
2025 J jnl
Deep Learning Surrogates for Real-Time Gas Emission Inversion.
CoRR
Thomas Newman, Christopher Nemeth, Matthew Jones, Philip Jonathan
2025 J jnl
Modelling Populations of Interaction Networks via Distance Metrics.
J. Mach. Learn. Res.
George Bolt, Simón Lunagómez, Christopher Nemeth
2024 J jnl
Diffusion Generative Modelling for Divide-and-Conquer MCMC.
CoRR
C. Trojan, Paul Fearnhead, Christopher Nemeth
2024 A* conf
Learning-Rate-Free Stochastic Optimization over Riemannian Manifolds.
ICML
Daniel Dodd, Louis Sharrock, Christopher Nemeth
2024 J jnl
Learning-Rate-Free Stochastic Optimization over Riemannian Manifolds.
CoRR
Daniel Dodd, Louis Sharrock, Christopher Nemeth
2024 A* conf
Markovian Flow Matching: Accelerating MCMC with Continuous Normalizing Flows.
NeurIPS
Alberto Cabezas, Louis Sharrock, Christopher Nemeth
2024 J jnl
Markovian Flow Matching: Accelerating MCMC with Continuous Normalizing Flows.
CoRR
Alberto Cabezas, Louis Sharrock, Christopher Nemeth
2024 J jnl
Position Paper: Bayesian Deep Learning in the Age of Large-Scale AI.
CoRR
Theodore Papamarkou, Maria Skoularidou, Konstantina Palla, Laurence Aitchison, Julyan Arbel, David B. 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 A* conf
Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI.
ICML
Theodore Papamarkou, Maria Skoularidou, Konstantina Palla, Laurence Aitchison, Julyan Arbel, David B. 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 J jnl
Scalable Monte Carlo for Bayesian Learning.
CoRR
Paul Fearnhead, Christopher Nemeth, Chris J. Oates, Chris Sherlock
2024 J jnl
Stochastic Gradient Piecewise Deterministic Monte Carlo Samplers.
CoRR
Paul Fearnhead, Sebastiano Grazzi, Christopher Nemeth, Gareth O. Roberts
2024 A conf
Tuning-Free Maximum Likelihood Training of Latent Variable Models via Coin Betting.
AISTATS
Louis Sharrock, Daniel Dodd, Christopher Nemeth
2023 A* conf
Coin Sampling: Gradient-Based Bayesian Inference without Learning Rates.
ICML
Louis Sharrock, Christopher Nemeth
2023 J jnl
Coin Sampling: Gradient-Based Bayesian Inference without Learning Rates.
CoRR
Louis Sharrock, Christopher Nemeth
2023 J jnl
CoinEM: Tuning-Free Particle-Based Variational Inference for Latent Variable Models.
CoRR
Louis Sharrock, Daniel Dodd, Christopher Nemeth
2023 J jnl
Efficient and generalizable tuning strategies for stochastic gradient MCMC.
Stat. Comput.
Jeremie Coullon, Leah F. South, Christopher Nemeth
2023 A* conf
Learning Rate Free Bayesian Inference in Constrained Domains.
NeurIPS
Louis Sharrock, Lester Mackey, Christopher Nemeth
2023 J jnl
Learning Rate Free Bayesian Inference in Constrained Domains.
CoRR
Louis Sharrock, Lester Mackey, Christopher Nemeth
2023 A conf
Preferential Subsampling for Stochastic Gradient Langevin Dynamics.
AISTATS
Srshti Putcha, Christopher Nemeth, Paul Fearnhead
2023 J jnl
Sequential estimation of temporally evolving latent space network models.
Comput. Stat. Data Anal.
Kathryn Turnbull, Christopher Nemeth, Matthew A. Nunes, Tyler H. McCormick
2023 A conf
Transport Elliptical Slice Sampling.
AISTATS
Alberto Cabezas, Christopher Nemeth
2022 J jnl
GaussianProcesses.jl: A Nonparametric Bayes Package for the
J. Stat. Softw.
Jamie Fairbrother, Christopher Nemeth, Maxime Rischard, Johanni Brea, Thomas Pinder
2022 J jnl
Preferential Subsampling for Stochastic Gradient Langevin Dynamics.
CoRR
Srshti Putcha, Christopher Nemeth, Paul Fearnhead
2022 J jnl
SGMCMCJax: a lightweight JAX library for stochastic gradient Markov chain Monte Carlo algorithms.
J. Open Source Softw.
Jeremie Coullon, Christopher Nemeth
2021 J jnl
Gaussian Processes on Hypergraphs.
CoRR
Thomas Pinder, Kathryn Turnbull, Christopher Nemeth, David Leslie
2020 J jnl
Stein Variational Gaussian Processes.
CoRR
Thomas Pinder, Christopher Nemeth, David Leslie
2019 J jnl
Control variates for stochastic gradient MCMC.
Stat. Comput.
Jack Baker, Paul Fearnhead, Emily B. Fox, Christopher Nemeth
2019 A* conf
Pseudo-Extended Markov chain Monte Carlo.
NeurIPS
Christopher Nemeth, Fredrik Lindsten, Maurizio Filippone, James Hensman
2019 J jnl
Stochastic Gradient MCMC for Nonlinear State Space Models.
CoRR
Christopher Aicher, Srshti Putcha, Christopher Nemeth, Paul Fearnhead, Emily B. Fox
2018 A* conf
Large-Scale Stochastic Sampling from the Probability Simplex.
NeurIPS
Jack Baker, Paul Fearnhead, Emily B. Fox, Christopher Nemeth
2018 J jnl
Large-Scale Stochastic Sampling from the Probability Simplex.
CoRR
Jack Baker, Paul Fearnhead, Emily B. Fox, Christopher Nemeth
2017 J jnl
Control Variates for Stochastic Gradient MCMC.
CoRR
Jack Baker, Paul Fearnhead, Emily B. Fox, Christopher Nemeth
2014 J jnl
Sequential Monte Carlo Methods for State and Parameter Estimation in Abruptly Changing Environments.
IEEE Trans. Signal Process.
Christopher Nemeth, Paul Fearnhead, Lyudmila Mihaylova
2013 J jnl
Erik Hollnagel: FRAM: The functional resonance analysis method, modeling complex socio-technical systems - 2012, Ashgate, ISBN 978-1-4094-4551-7, Paperback, £20.00, ISBN 978-1-4094-4552-4, Hardcover, £65.00.
Cogn. Technol. Work.
Christopher Nemeth
2012 C conf
Bearings-only tracking with particle filtering for joint parameter learning and state estimation.
FUSION
Christopher Nemeth, Paul Fearnhead, Lyudmila Mihaylova, Dave Vorley