Ali Siahkoohi - RankMe

41 papers A* 3A 1B 1Misc 1Journal 33Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Conditional neural control variates for variance reduction in Bayesian inverse problems. CoRR Ali Siahkoohi, Hyunwoo Oh
2026	J	`jnl`	Dual-space posterior sampling for Bayesian inference in constrained inverse problems. CoRR Ali Siahkoohi, Kamal Aghazade, Ali Gholami
2026	J	`jnl`	Hypernetwork-based approach for grid-independent functional data clustering. CoRR Anirudh Thatipelli, Ali Siahkoohi
2026	J	`jnl`	On the role of memorization in learned priors for geophysical inverse problems. CoRR Ali Siahkoohi, Davide Sabeddu
2024	J	`jnl`	ASPIRE: Iterative Amortized Posterior Inference for Bayesian Inverse Problems. CoRR Rafael Orozco, Ali Siahkoohi, Mathias Louboutin, Felix J. Herrmann
2024	J	`jnl`	Boomerang: Local sampling on image manifolds using diffusion models. Trans. Mach. Learn. Res. Lorenzo Luzi, Paul M. Mayer, Josue Casco-Rodriguez, Ali Siahkoohi, Richard G. Baraniuk
2024	J	`jnl`	InvertibleNetworks.jl: A Julia package for scalable normalizing flows. J. Open Source Softw. Rafael Orozco, Philipp A. Witte, Mathias Louboutin, Ali Siahkoohi, Gabrio Rizzuti, Bas Peters, Felix J. Herrmann
2024	J	`jnl`	Removing Bias from Maximum Likelihood Estimation with Model Autophagy. CoRR Paul M. Mayer, Lorenzo Luzi, Ali Siahkoohi, Don H. Johnson, Richard G. Baraniuk
2024	A*	`conf`	Self-Consuming Generative Models Go MAD. ICLR Sina Alemohammad, Josue Casco-Rodriguez, Lorenzo Luzi, Ahmed Imtiaz Humayun, Hossein Babaei, Daniel LeJeune, Ali Siahkoohi, Richard G. Baraniuk
2024	J	`jnl`	Taming Score-Based Diffusion Priors for Infinite-Dimensional Nonlinear Inverse Problems. CoRR Lorenzo Baldassari, Ali Siahkoohi, Josselin Garnier, Knut Solna, Maarten V. de Hoop
2024	Misc	`conf`	Titan: Bringing the Deep Image Prior to Implicit Representations. ICASSP Lorenzo Luzi, Daniel LeJeune, Ali Siahkoohi, Sina Alemohammad, Vishwanath Saragadam, Hossein Babaei, Naiming Liu, Zichao Wang, Richard G. Baraniuk
2023	B	`conf`	Adjoint operators enable fast and amortized machine learning based Bayesian uncertainty quantification. Image Processing Rafael Orozco, Ali Siahkoohi, Gabrio Rizzuti, Tristan van Leeuwen, Felix J. Herrmann
2023	—	`conf`	Amortized Normalizing Flows for Transcranial Ultrasound with Uncertainty Quantification. MIDL Rafael Orozco, Mathias Louboutin, Ali Siahkoohi, Gabrio Rizzuti, Tristan van Leeuwen, Felix Johan Herrmann
2023	J	`jnl`	Amortized Normalizing Flows for Transcranial Ultrasound with Uncertainty Quantification. CoRR Rafael Orozco, Mathias Louboutin, Ali Siahkoohi, Gabrio Rizzuti, Tristan van Leeuwen, Felix J. Herrmann
2023	A*	`conf`	Conditional score-based diffusion models for Bayesian inference in infinite dimensions. NeurIPS Lorenzo Baldassari, Ali Siahkoohi, Josselin Garnier, Knut Solna, Maarten V. de Hoop
2023	J	`jnl`	Conditional score-based diffusion models for Bayesian inference in infinite dimensions. CoRR Lorenzo Baldassari, Ali Siahkoohi, Josselin Garnier, Knut Solna, Maarten V. de Hoop
2023	J	`jnl`	InvertibleNetworks.jl: A Julia package for scalable normalizing flows. CoRR Rafael Orozco, Philipp A. Witte, Mathias Louboutin, Ali Siahkoohi, Gabrio Rizzuti, Bas Peters, Felix J. Herrmann
2023	J	`jnl`	Learned multiphysics inversion with differentiable programming and machine learning. CoRR 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
2023	J	`jnl`	Martian time-series unraveled: A multi-scale nested approach with factorial variational autoencoders. CoRR Ali Siahkoohi, Rudy Morel, Randall Balestriero, Erwan Allys, Grégory Sainton, Taichi Kawamura, Maarten V. de Hoop
2023	J	`jnl`	Refining Amortized Posterior Approximations using Gradient-Based Summary Statistics. CoRR Rafael Orozco, Ali Siahkoohi, Mathias Louboutin, Felix J. Herrmann
2023	J	`jnl`	Self-Consuming Generative Models Go MAD. CoRR Sina Alemohammad, Josue Casco-Rodriguez, Lorenzo Luzi, Ahmed Imtiaz Humayun, Hossein Babaei, Daniel LeJeune, Ali Siahkoohi, Richard G. Baraniuk
2023	A*	`conf`	Unearthing InSights into Mars: Unsupervised Source Separation with Limited Data. ICML Ali Siahkoohi, Rudy Morel, Maarten V. de Hoop, Erwan Allys, Grégory Sainton, Taichi Kawamura
2023	J	`jnl`	Unearthing InSights into Mars: unsupervised source separation with limited data. CoRR Ali Siahkoohi, Rudy Morel, Maarten V. de Hoop, Erwan Allys, Grégory Sainton, Taichi Kawamura
2022	J	`jnl`	Accelerating innovation with software abstractions for scalable computational geophysics. CoRR Mathias Louboutin, Philipp A. Witte, Ali Siahkoohi, Gabrio Rizzuti, Ziyi Yin, Rafael Orozco, Felix J. Herrmann
2022	J	`jnl`	Boomerang: Local sampling on image manifolds using diffusion models. CoRR Lorenzo Luzi, Ali Siahkoohi, Paul M. Mayer, Josue Casco-Rodriguez, Richard G. Baraniuk
2022	J	`jnl`	Learned coupled inversion for carbon sequestration monitoring and forecasting with Fourier neural operators. CoRR Ziyi Yin, Ali Siahkoohi, Mathias Louboutin, Felix J. Herrmann
2022	J	`jnl`	Reliable amortized variational inference with physics-based latent distribution correction. CoRR Ali Siahkoohi, Gabrio Rizzuti, Rafael Orozco, Felix J. Herrmann
2022	A	`conf`	Ultra-Low-Bitrate Speech Coding with Pretrained Transformers. INTERSPEECH Ali Siahkoohi, Michael Chinen, Tom Denton, W. Bastiaan Kleijn, Jan Skoglund
2022	J	`jnl`	Ultra-Low-Bitrate Speech Coding with Pretrained Transformers. CoRR Ali Siahkoohi, Michael Chinen, Tom Denton, W. Bastiaan Kleijn, Jan Skoglund
2022	J	`jnl`	Velocity continuation with Fourier neural operators for accelerated uncertainty quantification. CoRR Ali Siahkoohi, Mathias Louboutin, Felix J. Herrmann
2021	J	`jnl`	Learning by example: fast reliability-aware seismic imaging with normalizing flows. CoRR Ali Siahkoohi, Felix J. Herrmann
2021	J	`jnl`	Low-memory stochastic backpropagation with multi-channel randomized trace estimation. CoRR Mathias Louboutin, Ali Siahkoohi, Rongrong Wang, Felix J. Herrmann
2021	J	`jnl`	Preconditioned training of normalizing flows for variational inference in inverse problems. CoRR Ali Siahkoohi, Gabrio Rizzuti, Mathias Louboutin, Philipp A. Witte, Felix J. Herrmann
2020	J	`jnl`	A deep-learning based Bayesian approach to seismic imaging and uncertainty quantification. CoRR Ali Siahkoohi, Gabrio Rizzuti, Felix J. Herrmann
2020	J	`jnl`	Faster Uncertainty Quantification for Inverse Problems with Conditional Normalizing Flows. CoRR Ali Siahkoohi, Gabrio Rizzuti, Philipp A. Witte, Felix J. Herrmann
2020	J	`jnl`	Parameterizing uncertainty by deep invertible networks, an application to reservoir characterization. CoRR Gabrio Rizzuti, Ali Siahkoohi, Philipp A. Witte, Felix J. Herrmann
2020	J	`jnl`	Transfer learning in large-scale ocean bottom seismic wavefield reconstruction. CoRR Mi Zhang, Ali Siahkoohi, Felix J. Herrmann
2020	J	`jnl`	Uncertainty quantification in imaging and automatic horizon tracking: a Bayesian deep-prior based approach. CoRR Ali Siahkoohi, Gabrio Rizzuti, Felix J. Herrmann
2019	J	`jnl`	Learned imaging with constraints and uncertainty quantification. CoRR Felix J. Herrmann, Ali Siahkoohi, Gabrio Rizzuti
2019	J	`jnl`	Neural network augmented wave-equation simulation. CoRR Ali Siahkoohi, Mathias Louboutin, Felix J. Herrmann
2011	—	`conf`	A content-based digital image watermarking algorithm robust against JPEG compression. ISSPIT Amir Najafi, Ali Siahkoohi, Mohammad B. Shamsollahi