Summary of Learning Generalized Hamiltonians Using Fully Symplectic Mappings, by Harsh Choudhary et al.
Learning Generalized Hamiltonians using fully Symplectic Mappingsby Harsh Choudhary, Chandan Gupta, Vyacheslav kungrutsev, Melvin Leok,…
Learning Generalized Hamiltonians using fully Symplectic Mappingsby Harsh Choudhary, Chandan Gupta, Vyacheslav kungrutsev, Melvin Leok,…
Scale generalisation properties of extended scale-covariant and scale-invariant Gaussian derivative networks on image datasets with…
LASERS: LAtent Space Encoding for Representations with Sparsity for Generative Modelingby Xin Li, Anand SarwateFirst…
Score Forgetting Distillation: A Swift, Data-Free Method for Machine Unlearning in Diffusion Modelsby Tianqi Chen,…
Deep Learning tools to support deforestation monitoring in the Ivory Coast using SAR and Optical…
Cost-informed dimensionality reduction for structural digital twin technologiesby Aidan J. Hughes, Keith Worden, Nikolaos Dervilis,…
Federated Learning with Integrated Sensing, Communication, and Computation: Frameworks and Performance Analysisby Yipeng Liang, Qimei…
Spontaneous Informal Speech Dataset for Punctuation Restorationby Xing Yi Liu, Homayoon BeigiFirst submitted to arxiv…
Geometry Aware Meta-Learning Neural Network for Joint Phase and Precoder Optimization in RISby Dahlia Devapriya,…
LOLA – An Open-Source Massively Multilingual Large Language Modelby Nikit Srivastava, Denis Kuchelev, Tatiana Moteu…