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cs.LG2025
rETF-semiSL: Semi-Supervised Learning for Neural Collapse in Temporal Data
Yuhan Xie, William Cappelletti, Mahsa Shoaran +1
Deep neural networks for time series must capture complex temporal patterns, to effectively represent dynamic data. Self- and semi-supervised learning methods show promising result…
cs.LG2024
Deep End-to-End Survival Analysis with Temporal Consistency
Mariana Vargas Vieyra, Pascal Frossard
In this study, we present a novel Survival Analysis algorithm designed to efficiently handle large-scale longitudinal data. Our approach draws inspiration from Reinforcement Learni…