Shape-Informed Clustering of Multi-Dimensional Functional Data via Deep Functional Autoencoders
Fuente:
arXiv
Guardado en:
| Autores principales: | Singh, Samuel, Coyle, Shirley, Zhang, Mimi |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
A Data-Informed Variational Clustering Framework for Noisy High-Dimensional Data
por: Chen, Wan Ping
Publicado: (2026)
por: Chen, Wan Ping
Publicado: (2026)
Deep Functional Factor Models: Forecasting High-Dimensional Functional Time Series via Bayesian Nonparametric Factorization
por: Liu, Yirui, et al.
Publicado: (2023)
por: Liu, Yirui, et al.
Publicado: (2023)
Learning Geometrically-Informed Lyapunov Functions with Deep Diffeomorphic RBF Networks
por: Tesfazgi, Samuel, et al.
Publicado: (2025)
por: Tesfazgi, Samuel, et al.
Publicado: (2025)
Deep Invertible Autoencoders for Dimensionality Reduction of Dynamical Systems
por: Botteghi, Nicolò, et al.
Publicado: (2026)
por: Botteghi, Nicolò, et al.
Publicado: (2026)
Functional Autoencoder for Smoothing and Representation Learning
por: Wu, Sidi, et al.
Publicado: (2024)
por: Wu, Sidi, et al.
Publicado: (2024)
Unsupervised Deep Clustering of MNIST with Triplet-Enhanced Convolutional Autoencoders
por: Ansari, Md. Faizul Islam
Publicado: (2025)
por: Ansari, Md. Faizul Islam
Publicado: (2025)
An Introductory Survey to Autoencoder-based Deep Clustering -- Sandboxes for Combining Clustering with Deep Learning
por: Leiber, Collin, et al.
Publicado: (2025)
por: Leiber, Collin, et al.
Publicado: (2025)
funOCLUST: Clustering Functional Data with Outliers
por: Clark, Katharine M., et al.
Publicado: (2025)
por: Clark, Katharine M., et al.
Publicado: (2025)
Repetita Iuvant: Data Repetition Allows SGD to Learn High-Dimensional Multi-Index Functions
por: Arnaboldi, Luca, et al.
Publicado: (2024)
por: Arnaboldi, Luca, et al.
Publicado: (2024)
An Automated Data Mining Framework Using Autoencoders for Feature Extraction and Dimensionality Reduction
por: Liang, Yaxin, et al.
Publicado: (2024)
por: Liang, Yaxin, et al.
Publicado: (2024)
Data Augmentation with Variational Autoencoder for Imbalanced Dataset
por: Stocksieker, Samuel, et al.
Publicado: (2024)
por: Stocksieker, Samuel, et al.
Publicado: (2024)
Orthogonal Subspace Clustering: Enhancing High-Dimensional Data Analysis through Adaptive Dimensionality Reduction and Efficient Clustering
por: Wen, Qing-Yuan, et al.
Publicado: (2026)
por: Wen, Qing-Yuan, et al.
Publicado: (2026)
Integrating Random Effects in Variational Autoencoders for Dimensionality Reduction of Correlated Data
por: Simchoni, Giora, et al.
Publicado: (2024)
por: Simchoni, Giora, et al.
Publicado: (2024)
Rescaled Influence Functions: Accurate Data Attribution in High Dimension
por: Rubinstein, Ittai, et al.
Publicado: (2025)
por: Rubinstein, Ittai, et al.
Publicado: (2025)
Estimation and Inference for Causal Functions with Multiway Clustered Data
por: Liu, Nan, et al.
Publicado: (2024)
por: Liu, Nan, et al.
Publicado: (2024)
Functional BART with Shape Priors: A Bayesian Tree Approach to Constrained Functional Regression
por: Cao, Jiahao, et al.
Publicado: (2025)
por: Cao, Jiahao, et al.
Publicado: (2025)
Reparameterized Tensor Ring Functional Decomposition for Multi-Dimensional Data Recovery
por: Xu, Yangyang, et al.
Publicado: (2026)
por: Xu, Yangyang, et al.
Publicado: (2026)
Data-Driven Dimensional Synthesis of Diverse Planar Four-bar Function Generation Mechanisms via Direct Parameterization
por: Kim, Woon Ryong, et al.
Publicado: (2025)
por: Kim, Woon Ryong, et al.
Publicado: (2025)
Empowering Decision Trees via Shape Function Branching
por: Upadhya, Nakul, et al.
Publicado: (2025)
por: Upadhya, Nakul, et al.
Publicado: (2025)
Two-Dimensional Deep ReLU CNN Approximation for Korobov Functions: A Constructive Approach
por: Fang, Qin, et al.
Publicado: (2025)
por: Fang, Qin, et al.
Publicado: (2025)
Information-Theoretic Limits of Quantum Learning via Data Compression
por: Angrisani, Armando, et al.
Publicado: (2021)
por: Angrisani, Armando, et al.
Publicado: (2021)
Deep Learning Activation Functions: Fixed-Shape, Parametric, Adaptive, Stochastic, Miscellaneous, Non-Standard, Ensemble
por: Hammad, M. M.
Publicado: (2024)
por: Hammad, M. M.
Publicado: (2024)
NeuralFLoC: Neural Flow-Based Joint Registration and Clustering of Functional Data
por: Xiong, Xinyang, et al.
Publicado: (2026)
por: Xiong, Xinyang, et al.
Publicado: (2026)
DASVDD: Deep Autoencoding Support Vector Data Descriptor for Anomaly Detection
por: Hojjati, Hadi, et al.
Publicado: (2021)
por: Hojjati, Hadi, et al.
Publicado: (2021)
Deep Incomplete Multi-View Clustering via Hierarchical Imputation and Alignment
por: Du, Yiming, et al.
Publicado: (2026)
por: Du, Yiming, et al.
Publicado: (2026)
Sparse Autoencoders for Low-$N$ Protein Function Prediction and Design
por: Tsui, Darin, et al.
Publicado: (2025)
por: Tsui, Darin, et al.
Publicado: (2025)
TimeInf: Time Series Data Contribution via Influence Functions
por: Zhang, Yizi, et al.
Publicado: (2024)
por: Zhang, Yizi, et al.
Publicado: (2024)
Understanding Deep Gradient Leakage via Inversion Influence Functions
por: Zhang, Haobo, et al.
Publicado: (2023)
por: Zhang, Haobo, et al.
Publicado: (2023)
PITA: Physics-Informed Trajectory Autoencoder
por: Fischer, Johannes, et al.
Publicado: (2024)
por: Fischer, Johannes, et al.
Publicado: (2024)
Interpretable Deep Clustering for Tabular Data
por: Svirsky, Jonathan, et al.
Publicado: (2023)
por: Svirsky, Jonathan, et al.
Publicado: (2023)
ProtCLIP: Function-Informed Protein Multi-Modal Learning
por: Zhou, Hanjing, et al.
Publicado: (2024)
por: Zhou, Hanjing, et al.
Publicado: (2024)
MAFS: Multi-head Attention Feature Selection for High-Dimensional Data via Deep Fusion of Filter Methods
por: Sun, Xiaoyan, et al.
Publicado: (2026)
por: Sun, Xiaoyan, et al.
Publicado: (2026)
Stop Regressing: Training Value Functions via Classification for Scalable Deep RL
por: Farebrother, Jesse, et al.
Publicado: (2024)
por: Farebrother, Jesse, et al.
Publicado: (2024)
Hierarchical Sparse Representation Clustering for High-Dimensional Data Streams
por: Chen, Jie, et al.
Publicado: (2024)
por: Chen, Jie, et al.
Publicado: (2024)
Are Sparse Autoencoders Useful for Java Function Bug Detection?
por: Melo, Rui, et al.
Publicado: (2025)
por: Melo, Rui, et al.
Publicado: (2025)
Probability-Flow ODE in Infinite-Dimensional Function Spaces
por: Na, Kunwoo, et al.
Publicado: (2025)
por: Na, Kunwoo, et al.
Publicado: (2025)
Deep Neural Networks are Adaptive to Function Regularity and Data Distribution in Approximation and Estimation
por: Liu, Hao, et al.
Publicado: (2024)
por: Liu, Hao, et al.
Publicado: (2024)
Integrating Functionalities To A System Via Autoencoder Hippocampus Network
por: Luo, Siwei
Publicado: (2024)
por: Luo, Siwei
Publicado: (2024)
Adversarial Disentanglement by Backpropagation with Physics-Informed Variational Autoencoder
por: Koune, Ioannis Christoforos, et al.
Publicado: (2025)
por: Koune, Ioannis Christoforos, et al.
Publicado: (2025)
PIGPVAE: Physics-Informed Gaussian Process Variational Autoencoders
por: Spitieris, Michail, et al.
Publicado: (2025)
por: Spitieris, Michail, et al.
Publicado: (2025)
Ejemplares similares
-
A Data-Informed Variational Clustering Framework for Noisy High-Dimensional Data
por: Chen, Wan Ping
Publicado: (2026) -
Deep Functional Factor Models: Forecasting High-Dimensional Functional Time Series via Bayesian Nonparametric Factorization
por: Liu, Yirui, et al.
Publicado: (2023) -
Learning Geometrically-Informed Lyapunov Functions with Deep Diffeomorphic RBF Networks
por: Tesfazgi, Samuel, et al.
Publicado: (2025) -
Deep Invertible Autoencoders for Dimensionality Reduction of Dynamical Systems
por: Botteghi, Nicolò, et al.
Publicado: (2026) -
Functional Autoencoder for Smoothing and Representation Learning
por: Wu, Sidi, et al.
Publicado: (2024)