22 citations · 32 across the 7 of their papers we have counts for
7 papers
Priors learned from legacy reconstructions inherit undetectable overconfidence
Ali Siahkoohi, Sina Alemohammad
Where truths are scarce (e.g., seismic and medical imaging), learned priors in ill-posed inverse problems are trained on archives of legacy reconstructions---i.e., an older method'…
A lift for input-convex neural net training
Ali Siahkoohi, Anirudh Thatipelli
Input-convex neural nets parametrize the convex potentials of density models and transport maps, and their convexity requires the inter-layer weights to be non-negative. Projected…
Hypernetwork-based approach for grid-independent functional data clustering
Anirudh Thatipelli, Ali Siahkoohi
Functional data clustering is concerned with grouping functions that share similar structure, yet most existing methods implicitly operate on sampled grids, causing cluster assignm…
Improving Fairness and Mitigating MADness in Generative Models
Paul Mayer, Lorenzo Luzi, Ali Siahkoohi +2
Generative models unfairly penalize data belonging to minority classes, suffer from model autophagy disorder (MADness), and learn biased estimates of the underlying distribution pa…
Self-Consuming Generative Models Go MAD
Sina Alemohammad, Josue Casco-Rodriguez, Lorenzo Luzi +5
Seismic advances in generative AI algorithms for imagery, text, and other data types has led to the temptation to use synthetic data to train next-generation models. Repeating this…
TITAN: Bringing The Deep Image Prior to Implicit Representations
Lorenzo Luzi, Daniel LeJeune, Ali Siahkoohi +6
We study the interpolation capabilities of implicit neural representations (INRs) of images. In principle, INRs promise a number of advantages, such as continuous derivatives and a…
Boomerang: Local sampling on image manifolds using diffusion models
Lorenzo Luzi, Paul M Mayer, Josue Casco-Rodriguez +2
The inference stage of diffusion models can be seen as running a reverse-time diffusion stochastic differential equation, where samples from a Gaussian latent distribution are tran…