Papers Dictionary Learning
“Dictionary Learning” 태그가 달린 논문 823편 · 필터 해제
Weakly Supervised Convolutional Dictionary Learning for Multi-Label Classification
Convolutional Dictionary Learning (CDL) has emerged as a powerful approach for signal representation by learning translation-invariant features through convolution operations. While existing CDL methods are predominantly…
ClassificationDictionary LearningEnvironmental Sound ClassificationMulti-Label Classification+2Personalized Convolutional Dictionary Learning of Physiological Time Series
Human physiological signals tend to exhibit both global and local structures: the former are shared across a population, while the latter reflect inter-individual variability. For instance, kinetic measurements of the ga…
Dictionary LearningTime SeriesDynamic Dictionary Learning for Remote Sensing Image Segmentation
Remote sensing image segmentation faces persistent challenges in distinguishing morphologically similar categories and adapting to diverse scene variations. While existing methods rely on implicit representation learning…
Dictionary LearningImage SegmentationRepresentation LearningSemantic SegmentationUnraveling the Localized Latents: Learning Stratified Manifold Structures in LLM Embedding Space with Sparse Mixture-of-Experts
However, real-world data often exhibit complex local structures that can be challenging for single-model approaches with a smooth global manifold in the embedding space to unravel. In this work, we conjecture that in the…
Dictionary LearningMixture-of-ExpertsArchetypal SAE: Adaptive and Stable Dictionary Learning for Concept Extraction in Large Vision Models
Sparse Autoencoders (SAEs) have emerged as a powerful framework for machine learning interpretability, enabling the unsupervised decomposition of model representations into a dictionary of abstract, human-interpretable c…
Dictionary LearningDictionary-Learning-Based Data Pruning for System Identification
System identification is normally involved in augmenting time series data by time shifting and nonlinearisation (via polynomial basis), which introduce redundancy both feature-wise and sample-wise. Many research works fo…
Dictionary LearningTime SeriesInversion of Magnetic Data using Learned Dictionaries and Scale Space
Magnetic data inversion is an important tool in geophysics, used to infer subsurface magnetic susceptibility distributions from surface magnetic field measurements. This inverse problem is inherently ill-posed, character…
Dictionary LearningGeophysicsBoosting Adversarial Robustness and Generalization with Structural Prior
This work investigates a novel approach to boost adversarial robustness and generalization by incorporating structural prior into the design of deep learning models. Specifically, our study surprisingly reveals that exis…
Adversarial RobustnessDeep LearningDictionary LearningExploring the Limitations of Structured Orthogonal Dictionary Learning
This work is motivated by recent applications of structured dictionary learning, in particular when the dictionary is assumed to be the product of a few Householder atoms. We investigate the following two problems: 1) Ho…
Dictionary LearningMulti-field Visualization: Trait design and trait-induced merge trees
Feature level sets (FLS) have shown significant potential in the analysis of multi-field data by using traits defined in attribute space to specify features in the domain. In this work, we address key challenges in the p…
AttributeDictionary Learningfeature selectionMIRE: Matched Implicit Neural Representations
Implicit Neural Representations (INRs) are continuous function learners for conventional digital signal representations. With the aid of positional embeddings and/or exhaustively fine-tuned activation functions, INRs…
3D Shape RepresentationDictionary LearningEdge DetectionImage Inpainting+2A Zero-Shot Physics-Informed Dictionary Learning Approach for Sound Field Reconstruction
Sound field reconstruction aims to estimate pressure fields in areas lacking direct measurements. Existing techniques often rely on strong assumptions or face challenges related to data availability or the explicit model…
Dictionary LearningTowards scientific discovery with dictionary learning: Extracting biological concepts from microscopy foundation models
Dictionary learning (DL) has emerged as a powerful interpretability tool for large language models. By extracting known concepts (e.g., Golden-Gate Bridge) from human-interpretable data (e.g., text), sparse DL can elucid…
Dictionary Learningscientific discoveryDNF: Unconditional 4D Generation with Dictionary-based Neural Fields
While remarkable success has been achieved through diffusion-based 3D generative models for shapes, 4D generative modeling remains challenging due to the complexity of object deformations over time. We propose DNF, a new…
Dictionary LearningMonet: Mixture of Monosemantic Experts for Transformers
Understanding the internal computations of large language models (LLMs) is crucial for aligning them with human values and preventing undesirable behaviors like toxic content generation. However, mechanistic interpretabi…
Dictionary LearningMixture-of-ExpertsOn the relationship between Koopman operator approximations and neural ordinary differential equations for data-driven time-evolution predictions
This work explores the relationship between state space methods and Koopman operator-based methods for predicting the time-evolution of nonlinear dynamical systems. We demonstrate that extended dynamic mode decomposition…
Dictionary LearningTrajectory PredictionFeatures that Make a Difference: Leveraging Gradients for Improved Dictionary Learning
Sparse Autoencoders (SAEs) are a promising approach for extracting neural network representations by learning a sparse and overcomplete decomposition of the network's internal activations. However, SAEs are traditionally…
Dictionary LearningAlternative Learning Paradigms for Image Quality Transfer
Image Quality Transfer (IQT) aims to enhance the contrast and resolution of low-quality medical images, e.g. obtained from low-power devices, with rich information learned from higher quality images. In contrast to exist…
Dictionary LearningGroup Crosscoders for Mechanistic Analysis of Symmetry
We introduce group crosscoders, an extension of crosscoders that systematically discover and analyse symmetrical features in neural networks. While neural networks often develop equivariant representations without explic…
Dictionary LearningBeyond Label Attention: Transparency in Language Models for Automated Medical Coding via Dictionary Learning
Medical coding, the translation of unstructured clinical text into standardized medical codes, is a crucial but time-consuming healthcare practice. Though large language models (LLM) could automate the coding process and…
Dictionary LearningLanguage ModelingLanguage Modelling