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Ali Siahkoohi
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Journal Articles
- 2024
- [j1]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)
Conference and Workshop Papers
- 2024
- [c8]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: 6165-6169 - [c7]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 - 2023
- [c6]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: 31754-31772 - [c5]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: 332-349 - [c4]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 - [c3]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 - 2022
- [c2]Ali Siahkoohi, Michael Chinen, Tom Denton, W. Bastiaan Kleijn
, Jan Skoglund
:
Ultra-Low-Bitrate Speech Coding with Pretrained Transformers. INTERSPEECH 2022: 4421-4425 - 2011
- [c1]Amir Najafi
, Ali Siahkoohi
, Mohammad B. Shamsollahi:
A content-based digital image watermarking algorithm robust against JPEG compression. ISSPIT 2011: 432-437
Informal and Other Publications
- 2024
- [i27]Rafael Orozco, Ali Siahkoohi, Mathias Louboutin, Felix J. Herrmann:
ASPIRE: Iterative Amortized Posterior Inference for Bayesian Inverse Problems. CoRR abs/2405.05398 (2024) - [i26]Paul M. Mayer, Lorenzo Luzi, Ali Siahkoohi, Don H. Johnson, Richard G. Baraniuk:
Removing Bias from Maximum Likelihood Estimation with Model Autophagy. CoRR abs/2405.13977 (2024) - [i25]Lorenzo Baldassari, Ali Siahkoohi, Josselin Garnier, Knut Solna, Maarten V. de Hoop:
Taming Score-Based Diffusion Priors for Infinite-Dimensional Nonlinear Inverse Problems. CoRR abs/2405.15676 (2024) - 2023
- [i24]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 abs/2301.11981 (2023) - [i23]Rafael Orozco, Mathias Louboutin, Ali Siahkoohi, Gabrio Rizzuti, Tristan van Leeuwen, Felix J. Herrmann:
Amortized Normalizing Flows for Transcranial Ultrasound with Uncertainty Quantification. CoRR abs/2303.03478 (2023) - [i22]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 abs/2304.05592 (2023) - [i21]Rafael Orozco, Ali Siahkoohi, Mathias Louboutin, Felix J. Herrmann:
Refining Amortized Posterior Approximations using Gradient-Based Summary Statistics. CoRR abs/2305.08733 (2023) - [i20]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 abs/2305.16189 (2023) - [i19]Lorenzo Baldassari, Ali Siahkoohi, Josselin Garnier, Knut Solna, Maarten V. de Hoop:
Conditional score-based diffusion models for Bayesian inference in infinite dimensions. CoRR abs/2305.19147 (2023) - [i18]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 abs/2307.01850 (2023) - [i17]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 abs/2312.13480 (2023) - 2022
- [i16]Ali Siahkoohi, Mathias Louboutin, Felix J. Herrmann:
Velocity continuation with Fourier neural operators for accelerated uncertainty quantification. CoRR abs/2203.14386 (2022) - [i15]Ziyi Yin
, Ali Siahkoohi, Mathias Louboutin, Felix J. Herrmann:
Learned coupled inversion for carbon sequestration monitoring and forecasting with Fourier neural operators. CoRR abs/2203.14396 (2022) - [i14]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 abs/2203.15038 (2022) - [i13]Ali Siahkoohi, Michael Chinen, Tom Denton, W. Bastiaan Kleijn
, Jan Skoglund
:
Ultra-Low-Bitrate Speech Coding with Pretrained Transformers. CoRR abs/2207.02262 (2022) - [i12]Ali Siahkoohi, Gabrio Rizzuti, Rafael Orozco, Felix J. Herrmann:
Reliable amortized variational inference with physics-based latent distribution correction. CoRR abs/2207.11640 (2022) - [i11]Lorenzo Luzi, Ali Siahkoohi, Paul M. Mayer, Josue Casco-Rodriguez, Richard G. Baraniuk:
Boomerang: Local sampling on image manifolds using diffusion models. CoRR abs/2210.12100 (2022) - 2021
- [i10]Ali Siahkoohi, Gabrio Rizzuti, Mathias Louboutin, Philipp A. Witte, Felix J. Herrmann:
Preconditioned training of normalizing flows for variational inference in inverse problems. CoRR abs/2101.03709 (2021) - [i9]Ali Siahkoohi, Felix J. Herrmann:
Learning by example: fast reliability-aware seismic imaging with normalizing flows. CoRR abs/2104.06255 (2021) - [i8]Mathias Louboutin, Ali Siahkoohi, Rongrong Wang, Felix J. Herrmann:
Low-memory stochastic backpropagation with multi-channel randomized trace estimation. CoRR abs/2106.06998 (2021) - 2020
- [i7]Ali Siahkoohi, Gabrio Rizzuti, Felix J. Herrmann:
A deep-learning based Bayesian approach to seismic imaging and uncertainty quantification. CoRR abs/2001.04567 (2020) - [i6]Ali Siahkoohi, Gabrio Rizzuti, Felix J. Herrmann:
Uncertainty quantification in imaging and automatic horizon tracking: a Bayesian deep-prior based approach. CoRR abs/2004.00227 (2020) - [i5]Mi Zhang, Ali Siahkoohi, Felix J. Herrmann:
Transfer learning in large-scale ocean bottom seismic wavefield reconstruction. CoRR abs/2004.07388 (2020) - [i4]Gabrio Rizzuti, Ali Siahkoohi, Philipp A. Witte, Felix J. Herrmann:
Parameterizing uncertainty by deep invertible networks, an application to reservoir characterization. CoRR abs/2004.07871 (2020) - [i3]Ali Siahkoohi, Gabrio Rizzuti, Philipp A. Witte, Felix J. Herrmann:
Faster Uncertainty Quantification for Inverse Problems with Conditional Normalizing Flows. CoRR abs/2007.07985 (2020) - 2019
- [i2]Felix J. Herrmann, Ali Siahkoohi, Gabrio Rizzuti:
Learned imaging with constraints and uncertainty quantification. CoRR abs/1909.06473 (2019) - [i1]Ali Siahkoohi, Mathias Louboutin, Felix J. Herrmann:
Neural network augmented wave-equation simulation. CoRR abs/1910.00925 (2019)
Coauthor Index
aka: Felix Johan Herrmann
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