Ali Siahkoohi

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 35

Top Topics

Bayesian Inference

Inverse Problems

Maximum Likelihood Estimation

Diffusion Models

Top Venues

Publications

Paul M. Mayer, Lorenzo Luzi, Ali Siahkoohi, Don H. Johnson, Richard G. Baraniuk
Removing Bias from Maximum Likelihood Estimation with Model Autophagy. CoRR (2024)
Lorenzo Luzi, Daniel LeJeune, Ali Siahkoohi, Sina Alemohammad, Vishwanath Saragadam, Hossein Babaei, Naiming Liu, Zichao Wang, Richard G. Baraniuk
Titan: Bringing the Deep Image Prior to Implicit Representations. ICASSP (2024)
Lorenzo Luzi, Paul M. Mayer, Josue Casco-Rodriguez, Ali Siahkoohi, Richard G. Baraniuk
Boomerang: Local sampling on image manifolds using diffusion models. Trans. Mach. Learn. Res. 2024 (2024)
Lorenzo Baldassari, Ali Siahkoohi, Josselin Garnier, Knut Solna, Maarten V. de Hoop
Taming Score-Based Diffusion Priors for Infinite-Dimensional Nonlinear Inverse Problems. CoRR (2024)
Rafael Orozco, Ali Siahkoohi, Mathias Louboutin, Felix J. Herrmann
ASPIRE: Iterative Amortized Posterior Inference for Bayesian Inverse Problems. CoRR (2024)
Sina Alemohammad, Josue Casco-Rodriguez, Lorenzo Luzi, Ahmed Imtiaz Humayun, Hossein Babaei, Daniel LeJeune, Ali Siahkoohi, Richard G. Baraniuk
Self-Consuming Generative Models Go MAD. ICLR (2024)
Rafael Orozco, Ali Siahkoohi, Gabrio Rizzuti, Tristan van Leeuwen, Felix J. Herrmann
Adjoint operators enable fast and amortized machine learning based Bayesian uncertainty quantification. Medical Imaging: Image Processing (2023)
Ali Siahkoohi, Rudy Morel, Maarten V. de Hoop, Erwan Allys, Grégory Sainton, Taichi Kawamura
Unearthing InSights into Mars: unsupervised source separation with limited data. CoRR (2023)
Sina Alemohammad, Josue Casco-Rodriguez, Lorenzo Luzi, Ahmed Imtiaz Humayun, Hossein Babaei, Daniel LeJeune, Ali Siahkoohi, Richard G. Baraniuk
Self-Consuming Generative Models Go MAD. CoRR (2023)
Lorenzo Baldassari, Ali Siahkoohi, Josselin Garnier, Knut Solna, Maarten V. de Hoop
Conditional score-based diffusion models for Bayesian inference in infinite dimensions. CoRR (2023)
Rafael Orozco, Philipp A. Witte, Mathias Louboutin, Ali Siahkoohi, Gabrio Rizzuti, Bas Peters, Felix J. Herrmann
InvertibleNetworks.jl: A Julia package for scalable normalizing flows. CoRR (2023)
Rafael Orozco, Mathias Louboutin, Ali Siahkoohi, Gabrio Rizzuti, Tristan van Leeuwen, Felix Johan Herrmann
Amortized Normalizing Flows for Transcranial Ultrasound with Uncertainty Quantification. MIDL (2023)
Ali Siahkoohi, Rudy Morel, Maarten V. de Hoop, Erwan Allys, Grégory Sainton, Taichi Kawamura
Unearthing InSights into Mars: Unsupervised Source Separation with Limited Data. ICML (2023)
Ali Siahkoohi, Rudy Morel, Randall Balestriero, Erwan Allys, Grégory Sainton, Taichi Kawamura, Maarten V. de Hoop
Martian time-series unraveled: A multi-scale nested approach with factorial variational autoencoders. CoRR (2023)
Mathias Louboutin, Ziyi Yin, Rafael Orozco, Thomas J. Grady II, Ali Siahkoohi, Gabrio Rizzuti, Philipp A. Witte, Olav Møyner, Gerard J. Gorman, Felix J. Herrmann
Learned multiphysics inversion with differentiable programming and machine learning. CoRR (2023)
Lorenzo Baldassari, Ali Siahkoohi, Josselin Garnier, Knut Solna, Maarten V. de Hoop
Conditional score-based diffusion models for Bayesian inference in infinite dimensions. NeurIPS (2023)
Rafael Orozco, Mathias Louboutin, Ali Siahkoohi, Gabrio Rizzuti, Tristan van Leeuwen, Felix J. Herrmann
Amortized Normalizing Flows for Transcranial Ultrasound with Uncertainty Quantification. CoRR (2023)
Rafael Orozco, Ali Siahkoohi, Mathias Louboutin, Felix J. Herrmann
Refining Amortized Posterior Approximations using Gradient-Based Summary Statistics. CoRR (2023)
Ali Siahkoohi, Mathias Louboutin, Felix J. Herrmann
Velocity continuation with Fourier neural operators for accelerated uncertainty quantification. CoRR (2022)
Ziyi Yin, Ali Siahkoohi, Mathias Louboutin, Felix J. Herrmann
Learned coupled inversion for carbon sequestration monitoring and forecasting with Fourier neural operators. CoRR (2022)
Ali Siahkoohi, Gabrio Rizzuti, Rafael Orozco, Felix J. Herrmann
Reliable amortized variational inference with physics-based latent distribution correction. CoRR (2022)
Lorenzo Luzi, Ali Siahkoohi, Paul M. Mayer, Josue Casco-Rodriguez, Richard G. Baraniuk
Boomerang: Local sampling on image manifolds using diffusion models. CoRR (2022)
Ali Siahkoohi, Michael Chinen, Tom Denton, W. Bastiaan Kleijn, Jan Skoglund
Ultra-Low-Bitrate Speech Coding with Pretrained Transformers. CoRR (2022)
Mathias Louboutin, Philipp A. Witte, Ali Siahkoohi, Gabrio Rizzuti, Ziyi Yin, Rafael Orozco, Felix J. Herrmann
Accelerating innovation with software abstractions for scalable computational geophysics. CoRR (2022)
Ali Siahkoohi, Michael Chinen, Tom Denton, W. Bastiaan Kleijn, Jan Skoglund
Ultra-Low-Bitrate Speech Coding with Pretrained Transformers. INTERSPEECH (2022)
Ali Siahkoohi, Felix J. Herrmann
Learning by example: fast reliability-aware seismic imaging with normalizing flows. CoRR (2021)
Ali Siahkoohi, Gabrio Rizzuti, Mathias Louboutin, Philipp A. Witte, Felix J. Herrmann
Preconditioned training of normalizing flows for variational inference in inverse problems. CoRR (2021)
Mathias Louboutin, Ali Siahkoohi, Rongrong Wang, Felix J. Herrmann
Low-memory stochastic backpropagation with multi-channel randomized trace estimation. CoRR (2021)
Ali Siahkoohi, Gabrio Rizzuti, Felix J. Herrmann
A deep-learning based Bayesian approach to seismic imaging and uncertainty quantification. CoRR (2020)
Mi Zhang, Ali Siahkoohi, Felix J. Herrmann
Transfer learning in large-scale ocean bottom seismic wavefield reconstruction. CoRR (2020)
Ali Siahkoohi, Gabrio Rizzuti, Felix J. Herrmann
Uncertainty quantification in imaging and automatic horizon tracking: a Bayesian deep-prior based approach. CoRR (2020)
Gabrio Rizzuti, Ali Siahkoohi, Philipp A. Witte, Felix J. Herrmann
Parameterizing uncertainty by deep invertible networks, an application to reservoir characterization. CoRR (2020)
Ali Siahkoohi, Gabrio Rizzuti, Philipp A. Witte, Felix J. Herrmann
Faster Uncertainty Quantification for Inverse Problems with Conditional Normalizing Flows. CoRR (2020)
Ali Siahkoohi, Mathias Louboutin, Felix J. Herrmann
Neural network augmented wave-equation simulation. CoRR (2019)
Felix J. Herrmann, Ali Siahkoohi, Gabrio Rizzuti
Learned imaging with constraints and uncertainty quantification. CoRR (2019)
Amir Najafi, Ali Siahkoohi, Mohammad B. Shamsollahi
A content-based digital image watermarking algorithm robust against JPEG compression. ISSPIT (2011)