Imagen de Portada

PINE: Pipeline for Important Node Exploration in Attributed Networks

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Kovtun, Elizaveta, Makarenko, Maksim, Semenova, Natalia, Zaytsev, Alexey, Budennyy, Semen
Formato:	Preprint
Publicado:	2025
Materias:	Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Label Attention Network for Temporal Sets Prediction: You Were Looking at a Wrong Self-Attention
por: Kovtun, Elizaveta, et al.
Publicado: (2023)

Hiding Backdoors within Event Sequence Data via Poisoning Attacks
por: Ermilova, Alina, et al.
Publicado: (2023)

Embedding-Aware Feature Discovery: Bridging Latent Representations and Interpretable Features in Event Sequences
por: Sakhno, Artem, et al.
Publicado: (2026)

Uncertainty Estimation of Transformers' Predictions via Topological Analysis of the Attention Matrices
por: Kostenok, Elizaveta, et al.
Publicado: (2023)

On the Robustness of Machine Learning Models in Predicting Thermodynamic Properties: a Case of Searching for New Quasicrystal Approximants
por: Avilov, Fedor S., et al.
Publicado: (2024)

Uniting contrastive and generative learning for event sequences models
por: Yugay, Aleksandr, et al.
Publicado: (2024)

Foundation for unbiased cross-validation of spatio-temporal models for species distribution modeling
por: Koldasbayeva, Diana, et al.
Publicado: (2025)

From Variability to Stability: Advancing RecSys Benchmarking Practices
por: Shevchenko, Valeriy, et al.
Publicado: (2024)

Parameter-Efficient Neural CDEs via Implicit Function Jacobians
por: Kuleshov, Ilya, et al.
Publicado: (2025)

Beyond Simple Averaging: Improving NLP Ensemble Performance with Topological-Data-Analysis-Based Weighting
por: Proskura, Polina, et al.
Publicado: (2024)

Towards Foundation Time Series Model: To Synthesize Or Not To Synthesize?
por: Kuvshinova, Kseniia, et al.
Publicado: (2024)

Unleashing the power of novel conditional generative approaches for new materials discovery
por: Novitskiy, Lev, et al.
Publicado: (2024)

DeepRV: Accelerating Spatiotemporal Inference with Pre-trained Neural Priors
por: Navott, Jhonathan, et al.
Publicado: (2025)

Efficient Neural Controlled Differential Equations via Attentive Kernel Smoothing
por: Serov, Egor, et al.
Publicado: (2026)

U-Former ODE: Fast Probabilistic Forecasting of Irregular Time Series
por: Kuleshov, Ilya, et al.
Publicado: (2026)

Holistic Uncertainty Estimation For Open-Set Recognition
por: Erlygin, Leonid, et al.
Publicado: (2024)

Tokenised Flow Matching for Hierarchical Simulation Based Inference
por: Charles, Giovanni, et al.
Publicado: (2026)

Collusion Detection with Graph Neural Networks
por: Gomes, Lucas, et al.
Publicado: (2024)

A theoretical framework for self-supervised contrastive learning for continuous dependent data
por: Marusov, Alexander, et al.
Publicado: (2025)

WWAggr: A Window Wasserstein-based Aggregation for Ensemble Change Point Detection
por: Stepikin, Alexander, et al.
Publicado: (2025)

Language steering in latent space to mitigate unintended code-switching
por: Goncharov, Andrey, et al.
Publicado: (2025)

Normalizing self-supervised learning for provably reliable Change Point Detection
por: Bazarova, Alexandra, et al.
Publicado: (2024)

SmallML: Bayesian Transfer Learning for Small-Data Predictive Analytics
por: Leontev, Semen
Publicado: (2025)

Strong Linear Baselines Strike Back: Closed-Form Linear Models as Gaussian Process Conditional Density Estimators for TSAD
por: Yugay, Aleksandr, et al.
Publicado: (2026)

InDiD: Instant Disorder Detection via Representation Learning
por: Romanenkova, Evgenia, et al.
Publicado: (2021)

From Mice to Trains: Amortized Bayesian Inference on Graph Data
por: Jedhoff, Svenja, et al.
Publicado: (2026)

Modeling Topological Impact on Node Attribute Distributions in Attributed Graphs
por: Langari, Amirreza Shiralinasab, et al.
Publicado: (2026)

Attacks on Node Attributes in Graph Neural Networks
por: Xu, Ying, et al.
Publicado: (2024)

Concealed Adversarial attacks on neural networks for sequential data
por: Sokerin, Petr, et al.
Publicado: (2025)

Federated Learning for Non-factorizable Models using Deep Generative Prior Approximations
por: Hassan, Conor, et al.
Publicado: (2024)

Never Skip a Batch: Continuous Training of Temporal GNNs via Adaptive Pseudo-Supervision
por: Panyshev, Alexander, et al.
Publicado: (2025)

SMRS: advocating a unified reporting standard for surrogate models in the artificial intelligence era
por: Semenova, Elizaveta, et al.
Publicado: (2025)

Topological Metric for Unsupervised Embedding Quality Evaluation
por: Shestov, Aleksei, et al.
Publicado: (2025)

Transformer Neural Processes - Kernel Regression
por: Jenson, Daniel, et al.
Publicado: (2024)

Scalable Spatiotemporal Inference with Biased Scan Attention Transformer Neural Processes
por: Jenson, Daniel, et al.
Publicado: (2025)

Convolutional Neural Network and Adversarial Autoencoder in EEG images classification
por: Nasybullin, Albert, et al.
Publicado: (2026)

PROVCREATOR: Synthesizing Complex Heterogenous Graphs with Node and Edge Attributes
por: Wang, Tianhao, et al.
Publicado: (2025)

When an LLM is apprehensive about its answers -- and when its uncertainty is justified
por: Sychev, Petr, et al.
Publicado: (2025)

Complexity-aware fine-tuning
por: Goncharov, Andrey, et al.
Publicado: (2025)

Surrogate uncertainty estimation for your time series forecasting black-box: learn when to trust
por: Erlygin, Leonid, et al.
Publicado: (2023)