Scholar
Gergely Flamich
Google Scholar ID: 4Iw9TH8AAAAJ
Imperial College London
Machine Learning
Information Theory
Data Compression
Generative Models
Follow
Homepage
↗
Google Scholar
↗
Citations & Impact
All-time
Citations
398
H-index
9
i10-index
9
Publications
18
Co-authors
19
list available
Contact
Email
g.flamich@imperial.ac.uk
CV
Open ↗
GitHub
Open ↗
LinkedIn
Open ↗
Publications
8 items
Scalable Differentially Private Data Compression via Diffusion and Stochastic Codes
2026
Cited
0
Multi-Marginal Couplings for Metropolis-Hastings
2026
Cited
0
Rejection Sampling is Optimal for Relative Entropy Coding
2026
Cited
0
Singular Relative Entropy Coding with Bits-Back Rejection Sampling
2026
Cited
0
Data Compression with Stochastic Codes
2026
Cited
0
Data Compression with Relative Entropy Coding
2025
Cited
0
You Cannot Feed Two Birds with One Score: the Accuracy-Naturalness Tradeoff in Translation
2025
Cited
0
The Redundancy of Non-Singular Channel Simulation
2025
Cited
0
Resume (English only)
Co-authors
19 total
José Miguel Hernández-Lobato
Professor of Machine Learning, University of Cambridge
David Harris-Birtill
University of St Andrews, School of Computer Science
Co-author 3
Patrick Schrempf
Scientist, Canon Medical Research Europe & Honorary Research Fellow, University of St Andrews
Aaron Quigley
Science and Deputy Director of CSIRO’s Data61
Marton Havasi
Meta - FAIR
Jiajun He
PhD Student, University of Cambridge
Stratis Markou
Google DeepMind
