2 citations · 2 across the 2 of their papers we have counts for
5 papers
GEOPHYS: The Geometry of Physical Plausibility
Christian Internò, Alexander Pondaven, Habon Issa +8
While humans can identify physically implausible events within milliseconds, machine learning approaches addressing the same problem are extremely slow and expensive. They either r…
Pruning Federated Models through Loss Landscape Analysis and Client Agreement Scoring
Christian Internò, Elena Raponi, Markus Olhofer +5
The practical deployment of Federated Learning (FL) on resource-constrained devices is fundamentally limited by the high cost of training large models and the instability caused by…
The Observer Effect in World Models: Invasive Adaptation Corrupts Latent Physics
Christian Internò, Jumpei Yamaguchi, Loren Amdahl-Culleton +3
Determining whether neural models internalize physical laws as world models, rather than exploiting statistical shortcuts, remains challenging, especially under out-of-distribution…
AI-Generated Video Detection via Perceptual Straightening
Christian Internò, Robert Geirhos, Markus Olhofer +3
The rapid advancement of generative AI enables highly realistic synthetic videos, posing significant challenges for content authentication and raising urgent concerns about misuse.…
Federated Loss Exploration for Improved Convergence on Non-IID Data
Christian Internò, Markus Olhofer, Yaochu Jin +1
Federated learning (FL) has emerged as a groundbreaking paradigm in machine learning (ML), offering privacy-preserving collaborative model training across diverse datasets. Despite…