Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model. - Atilim Gunes Baydin; Lei Shao; Wahid Bhimji; Lukas Heinrich; Saeid Naderiparizi; Andreas Munk 001; Jialin Liu 002; Bradley Gram-Hansen; Gilles Louppe; Lawrence Meadows; Philip H. S. Torr; Victor W. Lee; et al. (NeurIPS, 2019)

Etalumis: bringing probabilistic programming to scientific simulators at scale. - Atilim Günes Baydin; Lei Shao; Wahid Bhimji; Lukas Heinrich; Lawrence Meadows; Jialin Liu 002; Andreas Munk 001; Saeid Naderiparizi; Bradley Gram-Hansen; Gilles Louppe; Mingfei Ma; Xiaohui Zhao; et al. (SC, 2019)

Coping With Simulators That Don't Always Return. - Andrew Warrington; Frank Wood; Saeid Naderiparizi (AISTATS, 2020)

Planning as Inference in Epidemiological Models. - Frank Wood; Andrew Warrington; Saeid Naderiparizi; Christian Weilbach; Vaden Masrani; William Harvey 002; Adam Scibior; Boyan Beronov; Seyed Ali Nasseri (CoRR, 2020)

Uncertainty in Neural Processes. - Saeid Naderiparizi; Kenny Chiu; Benjamin Bloem-Reddy; Frank Wood (CoRR, 2020)

Image Completion via Inference in Deep Generative Models. - William Harvey 002; Saeid Naderiparizi; Frank Wood (CoRR, 2021)

Planning as Inference in Epidemiological Dynamics Models. - Frank Wood; Andrew Warrington; Saeid Naderiparizi; Christian Weilbach; Vaden Masrani; William Harvey 002; Adam Scibior; Boyan Beronov; John Grefenstette; Duncan Campbell; Seyed Ali Nasseri (Frontiers Artif. Intell., 2021)

Amortized Rejection Sampling in Universal Probabilistic Programming. - Saeid Naderiparizi; Adam Scibior; Andreas Munk 001; Mehrdad Ghadiri; Atilim Gunes Baydin; Bradley J. Gram-Hansen; Christian A. Schröder de Witt; Robert Zinkov; Philip H. S. Torr; Tom Rainforth; Yee Whye Teh; Frank Wood (AISTATS, 2022)

Conditional Image Generation by Conditioning Variational Auto-Encoders. - William Harvey 002; Saeid Naderiparizi; Frank Wood (ICLR, 2022)

Flexible Diffusion Modeling of Long Videos. - William Harvey 002; Saeid Naderiparizi; Vaden Masrani; Christian Weilbach; Frank Wood (NeurIPS, 2022)

RangeAugment: Efficient Online Augmentation with Range Learning. - Sachin Mehta; Saeid Naderiparizi; Fartash Faghri; Maxwell Horton; Lailin Chen; Ali Farhadi; Oncel Tuzel; Mohammad Rastegari (CoRR, 2022)

Don't be so negative! Score-based Generative Modeling with Oracle-assisted Guidance. - Saeid Naderiparizi; Xiaoxuan Liang 001; Berend Zwartsenberg; Frank Wood (CoRR, 2023)

On Neural Process Pooling Operator Choice and Posterior Calibration. - Saeid Naderiparizi; Kenny Chiu; Benjamin Bloem-Reddy; Frank Wood (Canadian AI, 2024)

Don't be so Negative! Score-based Generative Modeling with Oracle-assisted Guidance. - Saeid Naderiparizi; Xiaoxuan Liang 001; Setareh Cohan; Berend Zwartsenberg; Frank Wood (ICML, 2024)

Nearest Neighbour Score Estimators for Diffusion Generative Models. - Matthew Niedoba; Dylan Green; Saeid Naderiparizi; Vasileios Lioutas; Jonathan Wilder Lavington; Xiaoxuan Liang 001; Yunpeng Liu 007; Ke Zhang; Setareh Dabiri; Adam Scibior; Berend Zwartsenberg; Frank Wood (ICML, 2024)

Semantically Consistent Video Inpainting with Conditional Diffusion Models. - Dylan Green; William Harvey 002; Saeid Naderiparizi; Matthew Niedoba; Yunpeng Liu 007; Xiaoxuan Liang 001; Jonathan Wilder Lavington; Ke Zhang; Vasileios Lioutas; Setareh Dabiri; Adam Scibior; Berend Zwartsenberg; et al. (CoRR, 2024)

TorchDriveEnv: A Reinforcement Learning Benchmark for Autonomous Driving with Reactive, Realistic, and Diverse Non-Playable Characters. - Jonathan Wilder Lavington; Ke Zhang; Vasileios Lioutas; Matthew Niedoba; Yunpeng Liu 007; Dylan Green; Saeid Naderiparizi; Xiaoxuan Liang 001; Setareh Dabiri; Adam Scibior; Berend Zwartsenberg; Frank Wood (CoRR, 2024)

Constrained Generative Modeling with Manually Bridged Diffusion Models. - Saeid Naderiparizi; Xiaoxuan Liang 001; Berend Zwartsenberg; Frank Wood (AAAI, 2025)