2 天之前 · This paper introduces self-supervised reflective learning (SSRL), an improved framework that addresses these limitations by enabling continuous refinement of pseudo …

By observing the learning behavior of representation learning and classifier learning as well as that of SSRL and supervised learning with noisy labels, we are the first to combine SSRL and …

more robust to noisy labels while representation is much more fragile, and by the recent advances of self-supervised representation learning (SSRL) technologies, we design a new method, i.e., …

2024年5月22日 · We show that our SSRL model meets or exceeds current state-of-the-art results on all Hits@k and mean reciprocal rank (MRR) metrics on four large benchmark KG datasets. …

2022年3月24日 · Self-supervised RL: A Unified Algorithmic Framework & Opensource Code Implementation of Algorithms for Self-supervised Reinforcement Leanring (SSRL) with …

2022年12月31日 · Thus, inspired by the observation that classifier is more robust to noisy labels while representation is much more fragile, and by the recent advances of self-supervised …

2023年10月20日 · 为了解决这个问题，我们提出了一种基于自监督表示学习的轨道表面缺陷检测（R-SSRL）设计框架。 受深度神经网络的启发，R-SSRL 基于卷积编码器-解码器神经网络进 …

Inspired by deep neural networks, the R-SSRL is organized based on a convolutional encoder–decoder neural network to segment rail defects. Also, it uses a novel self-supervised …

This is an official PyTorch implementation of "SSRL: Self-supervised Spatial-temporal Representation Learning for 3D Action recognition"

2024年9月23日 · Self-Supervised Representation Learning (SSRL) represents a burgeoning paradigm in machine learning, wherein a model acquires meaningful representations from …