Cover Image

Understanding Representation Learnability of Nonlinear Self-Supervised Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Yang, Ruofeng, Li, Xiangyuan, Jiang, Bo, Li, Shuai
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Graph Self-Supervised Learning with Learnable Structural and Positional Encodings
by: Wijesinghe, Asiri, et al.
Published: (2025)

DeepCell: Self-Supervised Multiview Fusion for Circuit Representation Learning
by: Shi, Zhengyuan, et al.
Published: (2025)

Self-Supervised Representation Learning for Geospatial Objects: A Survey
by: Chen, Yile, et al.
Published: (2024)

Mitigating Degree Bias in Graph Representation Learning with Learnable Structural Augmentation and Structural Self-Attention
by: Hoang, Van Thuy, et al.
Published: (2025)

Data-Driven Self-Supervised Graph Representation Learning
by: Samy, Ahmed E., et al.
Published: (2024)

The Impact of Semantic Pairs on Self-Supervised Representation Learning
by: Alkhalefi, Mohammad, et al.
Published: (2025)

Quantifying Representation Reliability in Self-Supervised Learning Models
by: Park, Young-Jin, et al.
Published: (2023)

Self-Supervised Learning of Disentangled Representations for Multivariate Time-Series
by: Chang, Ching, et al.
Published: (2024)

A Learnability Analysis on Neuro-Symbolic Learning
by: He, Hao-Yuan, et al.
Published: (2025)

CoRe-ECG: Advancing Self-Supervised Representation Learning for 12-Lead ECG via Contrastive and Reconstructive Synergy
by: Qin, Zehao, et al.
Published: (2026)

CGM-JEPA: Learning Consistent Continuous Glucose Monitor Representations via Predictive Self-Supervised Pretraining
by: Muhammad, Hada Melino, et al.
Published: (2026)

Occam's Razor for Self Supervised Learning: What is Sufficient to Learn Good Representations?
by: Ibrahim, Mark, et al.
Published: (2024)

Transformer-Based Representation Learning for Robust Gene Expression Modeling and Cancer Prognosis
by: Jiang, Shuai, et al.
Published: (2025)

Subgraph Gaussian Embedding Contrast for Self-Supervised Graph Representation Learning
by: Xie, Shifeng, et al.
Published: (2025)

Diffusion-Assisted Distillation for Self-Supervised Graph Representation Learning with MLPs
by: Ahn, Seong Jin, et al.
Published: (2025)

Context-Enhanced Multi-View Trajectory Representation Learning: Bridging the Gap through Self-Supervised Models
by: Qian, Tangwen, et al.
Published: (2024)

Self-Supervised Time-Series Anomaly Detection Using Learnable Data Augmentation
by: Choi, Kukjin, et al.
Published: (2024)

From Alignment to Prediction: A Study of Self-Supervised Learning and Predictive Representation Learning
by: Dutta, Mintu, et al.
Published: (2026)

LAC: Graph Contrastive Learning with Learnable Augmentation in Continuous Space
by: Lin, Zhenyu, et al.
Published: (2024)

PFML: Self-Supervised Learning of Time-Series Data Without Representation Collapse
by: Vaaras, Einari, et al.
Published: (2024)

ExGRG: Explicitly-Generated Relation Graph for Self-Supervised Representation Learning
by: Naseri, Mahdi, et al.
Published: (2024)

Online Preference-based Reinforcement Learning with Self-augmented Feedback from Large Language Model
by: Tu, Songjun, et al.
Published: (2024)

RL-BioAug: Label-Efficient Reinforcement Learning for Self-Supervised EEG Representation Learning
by: Lee, Cheol-Hui, et al.
Published: (2026)

Learning to Learn-at-Test-Time: Language Agents with Learnable Adaptation Policies
by: Lou, Zhanzhi, et al.
Published: (2026)

Clustering Properties of Self-Supervised Learning
by: Weng, Xi, et al.
Published: (2025)

Is Data Valuation Learnable and Interpretable?
by: Wu, Ou, et al.
Published: (2024)

Domain Knowledge is Power: Leveraging Physiological Priors for Self Supervised Representation Learning in Electrocardiography
by: Maghsoodi, Nooshin, et al.
Published: (2025)

Predictive Learning in Energy-based Models with Attractor Structures
by: Dong, Xingsi, et al.
Published: (2025)

Quantum-Enhanced Multi-Task Learning with Learnable Weighting for Pharmacokinetic and Toxicity Prediction
by: Zhang, Han, et al.
Published: (2025)

Continual Learning of Nonlinear Independent Representations
by: Sun, Boyang, et al.
Published: (2024)

Understanding Transferable Representation Learning and Zero-shot Transfer in CLIP
by: Chen, Zixiang, et al.
Published: (2023)

Beyond Weighted Summation: Learnable Nonlinear Aggregation Functions for Robust Artificial Neurons
by: Bozyigit, Berke Deniz
Published: (2026)

GSTBench: A Benchmark Study on the Transferability of Graph Self-Supervised Learning
by: Song, Yu, et al.
Published: (2025)

On the Universality of Self-Supervised Learning
by: Qiang, Wenwen, et al.
Published: (2024)

Multimodal Cardiovascular Risk Profiling Using Self-Supervised Learning of Polysomnography
by: He, Zhengxiao, et al.
Published: (2025)

Self-Supervised Disentangled Representation Learning for Robust Target Speech Extraction
by: Mu, Zhaoxi, et al.
Published: (2023)

Bolster Hallucination Detection via Prompt-Guided Data Augmentation
by: Li, Wenyun, et al.
Published: (2025)

Towards Understanding Multi-Round Large Language Model Reasoning: Approximability, Learnability and Generalizability
by: Xu, Chenhui, et al.
Published: (2025)

A Survey on Unlearnable Data
by: Li, Jiahao, et al.
Published: (2025)

Towards Automated Self-Supervised Learning for Truly Unsupervised Graph Anomaly Detection
by: Li, Zhong, et al.
Published: (2025)