22 citations · 32 across the 7 of their papers we have counts for
4 papers · 1 filter
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…