Paul Jeha — accepted AI-conference papers

2026

CREPE: Controlling diffusion with REPlica Exchange

Jiajun He, Paul Jeha, Peter Potaptchik, Leo Zhang, José Miguel Hernández-Lobato, Yuanqi Du +2

ICLR 2026poster

Inference-time control of diffusion models aims to steer model outputs to satisfy new constraints without retraining. Previous approaches have mostly relied on heuristic guidance or have been coupled with Sequential Monte Carlo (SMC) for bias correction. In this paper, we propose a flexible alternat…

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2022

PSA-GAN: Progressive Self Attention GANs for Synthetic Time Series

Paul Jeha, Michael Bohlke-Schneider, Pedro Mercado, Shubham Kapoor, Rajbir Singh Nirwan, Valentin Flunkert +2

ICLR 2022poster

Realistic synthetic time series data of sufficient length enables practical applications in time series modeling tasks, such as forecasting, but remains a challenge. In this paper we present PSA-GAN, a generative adversarial network (GAN) that generates long time series samples of high quality using…

Cited by 63 Source ↗PDF ↗code ↗Scholar ↗