Summary of Dropkan: Regularizing Kans by Masking Post-activations, By Mohammed Ghaith Altarabichi
DropKAN: Regularizing KANs by masking post-activationsby Mohammed Ghaith AltarabichiFirst submitted to arxiv on: 17 Jul…
DropKAN: Regularizing KANs by masking post-activationsby Mohammed Ghaith AltarabichiFirst submitted to arxiv on: 17 Jul…
SMLT-MUGC: Small, Medium, and Large Texts – Machine versus User-Generated Content Detection and Comparisonby Anjali…
Grounding and Evaluation for Large Language Models: Practical Challenges and Lessons Learned (Survey)by Krishnaram Kenthapadi,…
Abstraction Alignment: Comparing Model-Learned and Human-Encoded Conceptual Relationshipsby Angie Boggust, Hyemin Bang, Hendrik Strobelt, Arvind…
On Diversity in Discriminative Neural Networksby Brahim Oubaha, Claude Berrou, Xueyao Ji, Yehya Nasser, Raphaël…
A Unifying Post-Processing Framework for Multi-Objective Learn-to-Defer Problemsby Mohammad-Amin Charusaie, Samira SamadiFirst submitted to arxiv…
Scalable Monte Carlo for Bayesian Learningby Paul Fearnhead, Christopher Nemeth, Chris J. Oates, Chris SherlockFirst…
Proximity-based Self-Federated Learningby Davide Domini, Gianluca Aguzzi, Nicolas Farabegoli, Mirko Viroli, Lukas EsterleFirst submitted to…
SafePowerGraph: Safety-aware Evaluation of Graph Neural Networks for Transmission Power Gridsby Salah Ghamizi, Aleksandar Bojchevski,…
Semantic-Aware Representation of Multi-Modal Data for Data Ingress: A Literature Reviewby Pierre Lamart, Yinan Yu,…