Summary of Federated Learning For Traffic Flow Prediction with Synthetic Data Augmentation, by Fermin Orozco et al.
Federated Learning for Traffic Flow Prediction with Synthetic Data Augmentationby Fermin Orozco, Pedro Porto Buarque…
Federated Learning for Traffic Flow Prediction with Synthetic Data Augmentationby Fermin Orozco, Pedro Porto Buarque…
Analyzing and Mitigating Model Collapse in Rectified Flow Modelsby Huminhao Zhu, Fangyikang Wang, Tianyu Ding,…
Generative Zooby Tomasz Niewiadomski, Anastasios Yiannakidis, Hanz Cuevas-Velasquez, Soubhik Sanyal, Michael J. Black, Silvia Zuffi,…
From an Image to a Scene: Learning to Imagine the World from a Million 360…
SurvBETA: Ensemble-Based Survival Models Using Beran Estimators and Several Attention Mechanismsby Lev V. Utkin, Semen…
SimVS: Simulating World Inconsistencies for Robust View Synthesisby Alex Trevithick, Roni Paiss, Philipp Henzler, Dor…
Enhancing radioisotope identification in gamma spectra with transfer learningby Peter LalorFirst submitted to arxiv on:…
Exploring the Impact of Synthetic Data on Human Gesture Recognition Tasks Using GANsby George Kontogiannis,…
Towards Modeling Data Quality and Machine Learning Model Performanceby Usman Anjum, Chris Trentman, Elrod Caden,…
Multi-Armed Bandit Approach for Optimizing Training on Synthetic Databy Abdulrahman Kerim, Leandro Soriano Marcolino, Erickson…