Cover Image

Structured Contrastive Learning for Interpretable Latent Representations

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Shen, Zhengyang, Tu, Hua, Shi, Mayue
Format:	Preprint
Published:	2025
Subjects:	Machine Learning I.2.6; I.5.1
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Contrastive Representation Modeling for Anomaly Detection
by: Lunardi, Willian T., et al.
Published: (2025)

Efficient Action-Constrained Reinforcement Learning via Acceptance-Rejection Method and Augmented MDPs
by: Hung, Wei, et al.
Published: (2025)

AdaCap: An Adaptive Contrastive Approach for Small-Data Neural Networks
by: Belucci, Bruno, et al.
Published: (2025)

Learning to Land Anywhere: Transferable Generative Models for Aircraft Trajectories
by: Larsen, Olav Finne Praesteng, et al.
Published: (2025)

Latent Space Representation of Electricity Market Curves: Maintaining Structural Integrity
by: Výboh, Martin, et al.
Published: (2025)

Annot-Mix: Learning with Noisy Class Labels from Multiple Annotators via a Mixup Extension
by: Herde, Marek, et al.
Published: (2024)

The Spotlight Resonance Method: Resolving the Alignment of Embedded Activations
by: Bird, George
Published: (2025)

Mamba base PKD for efficient knowledge compression
by: Medina, José, et al.
Published: (2025)

ZClassifier: Temperature Tuning and Manifold Approximation via KL Divergence on Logit Space
by: Yong, Shim Soon
Published: (2025)

AGOP-IxG: A Gradient Covariance Filter for Local Feature Attribution on Tabular Data, with a Controlled Benchmark
by: Katakam, Raj Kiran Gupta
Published: (2026)

Nonparametric Partial Disentanglement via Mechanism Sparsity: Sparse Actions, Interventions and Sparse Temporal Dependencies
by: Lachapelle, Sébastien, et al.
Published: (2024)

Giving Sensors a Voice: Multimodal JEPA for Semantic Time-Series Embeddings
by: Dutta, Utsav, et al.
Published: (2026)

Subspace Geometry Governs Catastrophic Forgetting in Low-Rank Adaptation
by: Steele, Brady
Published: (2026)

Feature emergence via margin maximization: case studies in algebraic tasks
by: Morwani, Depen, et al.
Published: (2023)

Remaining Useful Life Estimation for Turbofan Engines: A Comparative Study of Classical, CNN, and LSTM Approaches
by: Goel, Astitva, et al.
Published: (2026)

SATORIS-N: Spectral Analysis based Traffic Observation Recovery via Informed Subspaces and Nuclear-norm minimization
by: Mohanty, Sampad, et al.
Published: (2026)

Entropy Aware Message Passing in Graph Neural Networks
by: Nazari, Philipp, et al.
Published: (2024)

Optimizing Latent Dimension Allocation in Hierarchical VAEs: Balancing Attenuation and Information Retention for OOD Detection
by: Williamson, Dane, et al.
Published: (2025)

Neural Reasoning Networks: Efficient Interpretable Neural Networks With Automatic Textual Explanations
by: Carrow, Stephen, et al.
Published: (2024)

Emergence of Quantised Representations Isolated to Anisotropic Functions
by: Bird, George
Published: (2025)

In-situ Autoguidance: Eliciting Self-Correction in Diffusion Models
by: Gu, Enhao, et al.
Published: (2025)

Listwise Direct Preference Optimization with Multi-Dimensional Preference Mixing
by: Sun, Yuhui, et al.
Published: (2025)

Contrastive Similarity Learning for Market Forecasting: The ContraSim Framework
by: Vinden, Nicholas, et al.
Published: (2025)

Massive Redundancy in Gradient Transport Enables Sparse Online Learning
by: Merin, Aur Shalev
Published: (2026)

Out of Distribution Detection for Efficient Continual Learning in Quality Prediction for Arc Welding
by: Hahn, Yannik, et al.
Published: (2025)

Step-E: A Differentiable Data Cleaning Framework for Robust Learning with Noisy Labels
by: Du, Wenzhang
Published: (2025)

Augmenting Replay in World Models for Continual Reinforcement Learning
by: Yang, Luke, et al.
Published: (2024)

CLGNN: A Contrastive Learning-based GNN Model for Betweenness Centrality Prediction on Temporal Graphs
by: Zhang, Tianming, et al.
Published: (2025)

CASE: Contrastive Activation for Saliency Estimation
by: Williamson, Dane, et al.
Published: (2025)

A Self-explainable Model of Long Time Series by Extracting Informative Structured Causal Patterns
by: Wang, Ziqian, et al.
Published: (2025)

When Does Margin Clamping Affect Training Variance? Dataset-Dependent Effects in Contrastive Forward-Forward Learning
by: Steier, Joshua
Published: (2026)

SeizureFormer: A Transformer Model for IEA-Based Seizure Risk Forecasting
by: Feng, Tianning, et al.
Published: (2025)

GCAD: Anomaly Detection in Multivariate Time Series from the Perspective of Granger Causality
by: Liu, Zehao, et al.
Published: (2025)

Optimizing Robustness and Accuracy in Mixture of Experts: A Dual-Model Approach
by: Zhang, Xu, et al.
Published: (2025)

Optimizing Inference in Transformer-Based Models: A Multi-Method Benchmark
by: Ho, Siu Hang, et al.
Published: (2025)

Aggregating Direct and Indirect Neighbors through Graph Linear Transformations
by: Rosenhoover, Marshall, et al.
Published: (2025)

QuIDE: Mastering the Quantized Intelligence Trade-off via Active Optimization
by: Jiang, Xiantao
Published: (2026)

Explicit Dropout: Deterministic Regularization for Transformer Architectures
by: Agrawal, Vidhi, et al.
Published: (2026)

Towards Automated Diagnosis of Inherited Arrhythmias: Combined Arrhythmia Classification Using Lead-Aware Spatial Attention Networks
by: Sigfstead, Sophie, et al.
Published: (2026)

Entropy Causal Graphs for Multivariate Time Series Anomaly Detection
by: Febrinanto, Falih Gozi, et al.
Published: (2023)