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- Konstantinos C. Zygalakis
aka: Konstantinos Zygalakis
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Publication search results
found 53 matches
- 2024
- Oliver M. Crook, Mihai Cucuringu, Tim Hurst, Carola-Bibiane Schönlieb, Matthew Thorpe, Konstantinos C. Zygalakis:
A linear transportation Lp distance for pattern recognition. Pattern Recognit. 147: 110080 (2024) - Tianming Bai, Aretha L. Teckentrup, Konstantinos C. Zygalakis:
Gaussian processes for Bayesian inverse problems associated with linear partial differential equations. Stat. Comput. 34(4): 139 (2024) - Teresa Klatzer, Paul Dobson, Yoann Altmann, Marcelo Pereyra, Jesús María Sanz-Serna, Konstantinos C. Zygalakis:
Accelerated Bayesian Imaging by Relaxed Proximal-Point Langevin Sampling. SIAM J. Imaging Sci. 17(2): 1078-1117 (2024) - Savvas Melidonis, Matthew Holden, Yoann Altmann, Marcelo Pereyra, Konstantinos C. Zygalakis:
Empirical Bayesian Imaging With Large-Scale Push-Forward Generative Priors. IEEE Signal Process. Lett. 31: 631-635 (2024) - Thomas Trigo Trindade, Konstantinos C. Zygalakis:
A hybrid tau-leap for simulating chemical kinetics with applications to parameter estimation. CoRR abs/2401.09097 (2024) - Xue Gong, Desmond J. Higham, Konstantinos Zygalakis, Ginestra Bianconi:
Higher-order Connection Laplacians for Directed Simplicial Complexes. CoRR abs/2402.07631 (2024) - 2023
- Armin Eftekhari, Luis Vargas, Konstantinos C. Zygalakis:
The forward-backward envelope for sampling with the overdamped Langevin algorithm. Stat. Comput. 33(4): 85 (2023) - Savvas Melidonis, Paul Dobson, Yoann Altmann, Marcelo Pereyra, Konstantinos Zygalakis:
Efficient Bayesian Computation for Low-Photon Imaging Problems. SIAM J. Imaging Sci. 16(3): 1195-1234 (2023) - Marcelo Pereyra, Luis Vargas Mieles, Konstantinos C. Zygalakis:
The Split Gibbs Sampler Revisited: Improvements to Its Algorithmic Structure and Augmented Target Distribution. SIAM J. Imaging Sci. 16(4): 2040-2071 (2023) - Hoomaan Maskan, Konstantinos Zygalakis, Alp Yurtsever:
A Variational Perspective on High-Resolution ODEs. NeurIPS 2023 - Tapio Helin, Andrew M. Stuart, Aretha L. Teckentrup, Konstantinos Zygalakis:
Introduction To Gaussian Process Regression In Bayesian Inverse Problems, With New ResultsOn Experimental Design For Weighted Error Measures. CoRR abs/2302.04518 (2023) - Paul Dobson, Jesús María Sanz-Serna, Konstantinos Zygalakis:
On the connections between optimization algorithms, Lyapunov functions, and differential equations: theory and insights. CoRR abs/2305.08658 (2023) - Tianming Bai, Aretha L. Teckentrup, Konstantinos C. Zygalakis:
Gaussian processes for Bayesian inverse problems associated with linear partial differential equations. CoRR abs/2307.08343 (2023) - Teresa Klatzer, Paul Dobson, Yoann Altmann, Marcelo Pereyra, Jesús María Sanz-Serna, Konstantinos C. Zygalakis:
Accelerated Bayesian imaging by relaxed proximal-point Langevin sampling. CoRR abs/2308.09460 (2023) - Stefano Di Giovacchino, Desmond J. Higham, Konstantinos Zygalakis:
Backward error analysis and the qualitative behaviour of stochastic optimization algorithms: Application to stochastic coordinate descent. CoRR abs/2309.02082 (2023) - Hoomaan Maskan, Konstantinos C. Zygalakis, Alp Yurtsever:
A Variational Perspective on High-Resolution ODEs. CoRR abs/2311.02002 (2023) - 2022
- Stefano Di Giovacchino, Desmond J. Higham, Konstantinos C. Zygalakis:
A Hierarchy of Network Models Giving Bistability Under Triadic Closure. Multiscale Model. Simul. 20(4): 1394-1410 (2022) - Matthew Holden, Marcelo Pereyra, Konstantinos C. Zygalakis:
Bayesian Imaging with Data-Driven Priors Encoded by Neural Networks. SIAM J. Imaging Sci. 15(2): 892-924 (2022) - Armin Eftekhari, Luis Vargas, Konstantinos Zygalakis:
The Forward-Backward Envelope for Sampling with the Overdamped Langevin Algorithm. CoRR abs/2201.09096 (2022) - Xue Gong, Desmond J. Higham, Konstantinos Zygalakis:
Generative Hypergraph Models and Spectral Embedding. CoRR abs/2207.13895 (2022) - Enrico Crovini, Simon L. Cotter, Konstantinos Zygalakis, Andrew B. Duncan:
Batch Bayesian Optimization via Particle Gradient Flows. CoRR abs/2209.04722 (2022) - 2021
- Jesús María Sanz-Serna, Konstantinos C. Zygalakis:
Wasserstein distance estimates for the distributions of numerical approximations to ergodic stochastic differential equations. J. Mach. Learn. Res. 22: 242:1-242:37 (2021) - Jesús María Sanz-Serna, Konstantinos C. Zygalakis:
The Connections Between Lyapunov Functions for Some Optimization Algorithms and Differential Equations. SIAM J. Numer. Anal. 59(3): 1542-1565 (2021) - Matthew Holden, Marcelo Pereyra, Konstantinos C. Zygalakis:
Bayesian Imaging With Data-Driven Priors Encoded by Neural Networks: Theory, Methods, and Algorithms. CoRR abs/2103.10182 (2021) - Jesús María Sanz-Serna, Konstantinos C. Zygalakis:
Wasserstein distance estimates for the distributions of numerical approximations to ergodic stochastic differential equations. CoRR abs/2104.12384 (2021) - Xue Gong, Desmond John Higham, Konstantinos Zygalakis:
Directed Network Laplacians and Random Graph Models. CoRR abs/2107.03026 (2021) - Stefano Di Giovacchino, Desmond J. Higham, Konstantinos C. Zygalakis:
A Hierarchy of Network Models Giving Bistability Under Triadic Closure. CoRR abs/2111.05715 (2021) - 2020
- Michael B. Giles, Mateusz B. Majka, Lukasz Szpruch, Sebastian J. Vollmer, Konstantinos C. Zygalakis:
Multi-level Monte Carlo methods for the approximation of invariant measures of stochastic differential equations. Stat. Comput. 30(3): 507-524 (2020) - Marcelo Pereyra, Luis Vargas Mieles, Konstantinos C. Zygalakis:
Accelerating Proximal Markov Chain Monte Carlo by Using an Explicit Stabilized Method. SIAM J. Imaging Sci. 13(2): 905-935 (2020) - Jesús María Sanz-Serna, Konstantinos C. Zygalakis:
Contractivity of Runge-Kutta Methods for Convex Gradient Systems. SIAM J. Numer. Anal. 58(4): 2079-2092 (2020)
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