Konstantinos Zygalakis

19 papers A* 1Journal 17Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Batch Bayesian Optimization via Particle Gradient Flows. SIAM/ASA J. Uncertain. Quantification Enrico Crovini, Simon L. Cotter, Konstantinos Zygalakis, Andrew B. Duncan
2026	J	`jnl`	Deep unfolding of MCMC kernels: scalable, modular & explainable GANs for high-dimensional posterior sampling. CoRR Jonathan Spence, Tobías I. Liaudat, Konstantinos Zygalakis, Marcelo Pereyra
2025	J	`jnl`	Hypothesis Testing in Imaging Inverse Problems. CoRR Yiming Xi, Konstantinos Zygalakis, Marcelo Pereyra
2025	J	`jnl`	Sampling as Bandits: Evaluation-Efficient Design for Black-Box Densities. CoRR Takuo Matsubara, Andrew B. Duncan, Simon L. Cotter, Konstantinos Zygalakis
2024	J	`jnl`	Bayesian computation with generative diffusion models by Multilevel Monte Carlo. CoRR Abdul-Lateef Haji-Ali, Marcelo Pereyra, Luke Shaw, Konstantinos Zygalakis
2024	J	`jnl`	Higher-order Connection Laplacians for Directed Simplicial Complexes. CoRR Xue Gong, Desmond J. Higham, Konstantinos Zygalakis, Ginestra Bianconi
2023	A*	`conf`	A Variational Perspective on High-Resolution ODEs. NeurIPS Hoomaan Maskan, Konstantinos Zygalakis, Alp Yurtsever
2023	J	`jnl`	Backward error analysis and the qualitative behaviour of stochastic optimization algorithms: Application to stochastic coordinate descent. CoRR Stefano Di Giovacchino, Desmond J. Higham, Konstantinos Zygalakis
2023	J	`jnl`	Efficient Bayesian Computation for Low-Photon Imaging Problems. SIAM J. Imaging Sci. Savvas Melidonis, Paul Dobson, Yoann Altmann, Marcelo Pereyra, Konstantinos Zygalakis
2023	J	`jnl`	Introduction To Gaussian Process Regression In Bayesian Inverse Problems, With New ResultsOn Experimental Design For Weighted Error Measures. CoRR Tapio Helin, Andrew M. Stuart, Aretha L. Teckentrup, Konstantinos Zygalakis
2023	J	`jnl`	On the connections between optimization algorithms, Lyapunov functions, and differential equations: theory and insights. CoRR Paul Dobson, Jesús María Sanz-Serna, Konstantinos Zygalakis
2022	J	`jnl`	Batch Bayesian Optimization via Particle Gradient Flows. CoRR Enrico Crovini, Simon L. Cotter, Konstantinos Zygalakis, Andrew B. Duncan
2022	J	`jnl`	Generative Hypergraph Models and Spectral Embedding. CoRR Xue Gong, Desmond J. Higham, Konstantinos Zygalakis
2022	J	`jnl`	The Forward-Backward Envelope for Sampling with the Overdamped Langevin Algorithm. CoRR Armin Eftekhari, Luis Vargas, Konstantinos Zygalakis
2021	J	`jnl`	Directed Network Laplacians and Random Graph Models. CoRR Xue Gong, Desmond John Higham, Konstantinos Zygalakis
2020	J	`jnl`	Implicit Regularization in Matrix Sensing: A Geometric View Leads to Stronger Results. CoRR Armin Eftekhari, Konstantinos Zygalakis
2017	J	`jnl`	Statistical analysis of differential equations: introducing probability measures on numerical solutions. Stat. Comput. Patrick R. Conrad, Mark A. Girolami, Simo Särkkä, Andrew M. Stuart, Konstantinos Zygalakis
2016	—	`conf`	Probabilistic Linear Multistep Methods. NIPS Onur Teymur, Konstantinos Zygalakis, Ben Calderhead
2016	J	`jnl`	Probabilistic Linear Multistep Methods. CoRR Onur Teymur, Konstantinos Zygalakis, Ben Calderhead