Saeid Naderiparizi

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 19

Top Topics

Image Generation

Posterior Probability

Probabilistic Inference

Generative Model

Top Venues

Publications

Matthew Niedoba, Dylan Green, Saeid Naderiparizi, Vasileios Lioutas, Jonathan Wilder Lavington, Xiaoxuan Liang, Yunpeng Liu, Ke Zhang, Setareh Dabiri, Adam Scibior, Berend Zwartsenberg, Frank Wood
Nearest Neighbour Score Estimators for Diffusion Generative Models. CoRR (2024)
Dylan Green, William Harvey, Saeid Naderiparizi, Matthew Niedoba, Yunpeng Liu, Xiaoxuan Liang, Jonathan Wilder Lavington, Ke Zhang, Vasileios Lioutas, Setareh Dabiri, Adam Scibior, Berend Zwartsenberg, Frank Wood
Semantically Consistent Video Inpainting with Conditional Diffusion Models. CoRR (2024)
Jonathan Wilder Lavington, Ke Zhang, Vasileios Lioutas, Matthew Niedoba, Yunpeng Liu, Dylan Green, Saeid Naderiparizi, Xiaoxuan Liang, Setareh Dabiri, Adam Scibior, Berend Zwartsenberg, Frank Wood
TorchDriveEnv: A Reinforcement Learning Benchmark for Autonomous Driving with Reactive, Realistic, and Diverse Non-Playable Characters. CoRR (2024)
Saeid Naderiparizi, Xiaoxuan Liang, Berend Zwartsenberg, Frank Wood
Don't be so negative! Score-based Generative Modeling with Oracle-assisted Guidance. CoRR (2023)
Sachin Mehta, Saeid Naderiparizi, Fartash Faghri, Maxwell Horton, Lailin Chen, Ali Farhadi, Oncel Tuzel, Mohammad Rastegari
RangeAugment: Efficient Online Augmentation with Range Learning. CoRR (2022)
William Harvey, Saeid Naderiparizi, Vaden Masrani, Christian Weilbach, Frank Wood
Flexible Diffusion Modeling of Long Videos. NeurIPS (2022)
William Harvey, Saeid Naderiparizi, Frank Wood
Conditional Image Generation by Conditioning Variational Auto-Encoders. ICLR (2022)
Saeid Naderiparizi, Adam Scibior, Andreas Munk, 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
Amortized Rejection Sampling in Universal Probabilistic Programming. AISTATS (2022)
William Harvey, Saeid Naderiparizi, Vaden Masrani, Christian Weilbach, Frank Wood
Flexible Diffusion Modeling of Long Videos. CoRR (2022)
William Harvey, Saeid Naderiparizi, Frank Wood
Image Completion via Inference in Deep Generative Models. CoRR (2021)
Frank Wood, Andrew Warrington, Saeid Naderiparizi, Christian Weilbach, Vaden Masrani, William Harvey, Adam Scibior, Boyan Beronov, John Grefenstette, Duncan Campbell, Seyed Ali Nasseri
Planning as Inference in Epidemiological Dynamics Models. Frontiers Artif. Intell. 4 (2021)
Saeid Naderiparizi, Kenny Chiu, Benjamin Bloem-Reddy, Frank Wood
Uncertainty in Neural Processes. CoRR (2020)
Andrew Warrington, Frank Wood, Saeid Naderiparizi
Coping With Simulators That Don't Always Return. AISTATS (2020)
Andrew Warrington, Saeid Naderiparizi, Frank Wood
Coping With Simulators That Don't Always Return. CoRR (2020)
Frank Wood, Andrew Warrington, Saeid Naderiparizi, Christian Weilbach, Vaden Masrani, William Harvey, Adam Scibior, Boyan Beronov, Ali Nasseri
Planning as Inference in Epidemiological Models. CoRR (2020)
Atilim Günes Baydin, Lei Shao, Wahid Bhimji, Lukas Alexander Heinrich, Lawrence Meadows, Jialin Liu, Andreas Munk, Saeid Naderiparizi, Bradley Gram-Hansen, Gilles Louppe, Mingfei Ma, Xiaohui Zhao, Philip H. S. Torr, Victor W. Lee, Kyle Cranmer, Prabhat, Frank Wood
Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale. CoRR (2019)
Atilim Günes Baydin, Lei Shao, Wahid Bhimji, Lukas Alexander Heinrich, Lawrence Meadows, Jialin Liu, Andreas Munk, Saeid Naderiparizi, Bradley Gram-Hansen, Gilles Louppe, Mingfei Ma, Xiaohui Zhao, Philip H. S. Torr, Victor W. Lee, Kyle Cranmer, Prabhat, Frank Wood
Etalumis: bringing probabilistic programming to scientific simulators at scale. SC (2019)
Saeid Naderiparizi, Adam Scibior, Andreas Munk, Mehrdad Ghadiri, Atilim Günes Baydin, Bradley Gram-Hansen, Christian Schröder de Witt, Robert Zinkov, Philip H. S. Torr, Tom Rainforth, Yee Whye Teh, Frank Wood
Amortized Rejection Sampling in Universal Probabilistic Programming. CoRR (2019)
Atilim Gunes Baydin, Lei Shao, Wahid Bhimji, Lukas Alexander Heinrich, Saeid Naderiparizi, Andreas Munk, Jialin Liu, Bradley Gram-Hansen, Gilles Louppe, Lawrence Meadows, Philip H. S. Torr, Victor W. Lee, Kyle Cranmer, Prabhat, Frank Wood
Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model. NeurIPS (2019)