activity
20202023
most citedThe Curse of Recursion: Training on Generated Data Makes Models Forget

158 citations · 165 across the 2 of their papers we have counts for

collaborators

5 papers

cs.LG2023★ 158 cited

The Curse of Recursion: Training on Generated Data Makes Models Forget

Ilia Shumailov, Zakhar Shumaylov, Yiren Zhao +3

Stable Diffusion revolutionised image creation from descriptive text. GPT-2, GPT-3(.5) and GPT-4 demonstrated astonishing performance across a variety of language tasks. ChatGPT in…

gr-qc2022★ 7 cited

Quantum initial conditions for curved inflating universes

Mary I. Letey, Zakhar Shumaylov, Fruzsina J. Agocs +3

We discuss the challenges of motivating, constructing, and quantizing a canonically normalized inflationary perturbation in spatially curved universes. We show that this has histor…

astro-ph.CO2021

Primordial power spectra from -inflation with curvature

Zakhar Shumaylov, Will Handley

We investigate the primordial power spectra for general kinetic inflation models that support a period of kinetic dominance in the case of curved universes. We present derivations…

cs.LG2021

Manipulating SGD with Data Ordering Attacks

Ilia Shumailov, Zakhar Shumaylov, Dmitry Kazhdan +4

Machine learning is vulnerable to a wide variety of attacks. It is now well understood that by changing the underlying data distribution, an adversary can poison the model trained…

cs.LG2020

Learned convex regularizers for inverse problems

Subhadip Mukherjee, Sören Dittmer, Zakhar Shumaylov +3

We consider the variational reconstruction framework for inverse problems and propose to learn a data-adaptive input-convex neural network (ICNN) as the regularization functional.…