WWAggr: A Window Wasserstein-based Aggregation for Ensemble Change Point Detection
Fuente:
arXiv
Saved in:
| Main Authors: | Stepikin, Alexander, Romanenkova, Evgenia, Zaytsev, Alexey |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Normalizing self-supervised learning for provably reliable Change Point Detection
by: Bazarova, Alexandra, et al.
Published: (2024)
by: Bazarova, Alexandra, et al.
Published: (2024)
InDiD: Instant Disorder Detection via Representation Learning
by: Romanenkova, Evgenia, et al.
Published: (2021)
by: Romanenkova, Evgenia, et al.
Published: (2021)
Learning Transactions Representations for Information Management in Banks: Mastering Local, Global, and External Knowledge
by: Bazarova, Alexandra, et al.
Published: (2024)
by: Bazarova, Alexandra, et al.
Published: (2024)
DeNOTS: Stable Deep Neural ODEs for Time Series
by: Kuleshov, Ilya, et al.
Published: (2024)
by: Kuleshov, Ilya, et al.
Published: (2024)
A theoretical framework for self-supervised contrastive learning for continuous dependent data
by: Marusov, Alexander, et al.
Published: (2025)
by: Marusov, Alexander, et al.
Published: (2025)
Parameter-Efficient Neural CDEs via Implicit Function Jacobians
by: Kuleshov, Ilya, et al.
Published: (2025)
by: Kuleshov, Ilya, et al.
Published: (2025)
Holistic Uncertainty Estimation For Open-Set Recognition
by: Erlygin, Leonid, et al.
Published: (2024)
by: Erlygin, Leonid, et al.
Published: (2024)
Concealed Adversarial attacks on neural networks for sequential data
by: Sokerin, Petr, et al.
Published: (2025)
by: Sokerin, Petr, et al.
Published: (2025)
Surrogate uncertainty estimation for your time series forecasting black-box: learn when to trust
by: Erlygin, Leonid, et al.
Published: (2023)
by: Erlygin, Leonid, et al.
Published: (2023)
Online Neural Networks for Change-Point Detection
by: Hushchyn, Mikhail, et al.
Published: (2020)
by: Hushchyn, Mikhail, et al.
Published: (2020)
A Natural Gas Consumption Forecasting System for Continual Learning Scenarios based on Hoeffding Trees with Change Point Detection Mechanism
by: Svoboda, Radek, et al.
Published: (2023)
by: Svoboda, Radek, et al.
Published: (2023)
Adapt, Agree, Aggregate: Semi-Supervised Ensemble Labeling for Graph Convolutional Networks
by: Abdolali, Maryam, et al.
Published: (2025)
by: Abdolali, Maryam, et al.
Published: (2025)
Drift-Aware Variational Autoencoder-based Anomaly Detection with Two-level Ensembling
by: Li, Jin, et al.
Published: (2026)
by: Li, Jin, et al.
Published: (2026)
A Graph-based Framework for Online Time Series Anomaly Detection Using Model Ensemble
by: Yu, Zewei, et al.
Published: (2026)
by: Yu, Zewei, et al.
Published: (2026)
From Variability to Stability: Advancing RecSys Benchmarking Practices
by: Shevchenko, Valeriy, et al.
Published: (2024)
by: Shevchenko, Valeriy, et al.
Published: (2024)
Wasserstein Policy Optimization
by: Pfau, David, et al.
Published: (2025)
by: Pfau, David, et al.
Published: (2025)
Private Wasserstein Distance
by: Li, Wenqian, et al.
Published: (2024)
by: Li, Wenqian, et al.
Published: (2024)
Offline Imitation from Observation via Primal Wasserstein State Occupancy Matching
by: Yan, Kai, et al.
Published: (2023)
by: Yan, Kai, et al.
Published: (2023)
Beyond Simple Averaging: Improving NLP Ensemble Performance with Topological-Data-Analysis-Based Weighting
by: Proskura, Polina, et al.
Published: (2024)
by: Proskura, Polina, et al.
Published: (2024)
Improved Training of Physics-Informed Neural Networks with Model Ensembles
by: Haitsiukevich, Katsiaryna, et al.
Published: (2022)
by: Haitsiukevich, Katsiaryna, et al.
Published: (2022)
Conformal Prediction for Time-series Forecasting with Change Points
by: Sun, Sophia, et al.
Published: (2025)
by: Sun, Sophia, et al.
Published: (2025)
Tree-Sliced Wasserstein Distance: A Geometric Perspective
by: Tran, Viet-Hoang, et al.
Published: (2024)
by: Tran, Viet-Hoang, et al.
Published: (2024)
Detecting and Mitigating the Correct-Answer Extinction Window in Test-Time Reinforcement Learning with Majority Voting
by: Lin, Hongxiang, et al.
Published: (2026)
by: Lin, Hongxiang, et al.
Published: (2026)
Spherical Tree-Sliced Wasserstein Distance
by: Tran, Viet-Hoang, et al.
Published: (2025)
by: Tran, Viet-Hoang, et al.
Published: (2025)
Wasserstein Distances, Neuronal Entanglement, and Sparsity
by: Sawmya, Shashata, et al.
Published: (2024)
by: Sawmya, Shashata, et al.
Published: (2024)
Canonical Variates in Wasserstein Metric Space
by: Li, Jia, et al.
Published: (2024)
by: Li, Jia, et al.
Published: (2024)
A Novel DDPM-based Ensemble Approach for Energy Theft Detection in Smart Grids
by: Yuan, Xun, et al.
Published: (2023)
by: Yuan, Xun, et al.
Published: (2023)
Financial Fraud Detection Using Explainable AI and Stacking Ensemble Methods
by: Almalki, Fahad, et al.
Published: (2025)
by: Almalki, Fahad, et al.
Published: (2025)
Adaptive Ensembles of Fine-Tuned Transformers for LLM-Generated Text Detection
by: Lai, Zhixin, et al.
Published: (2024)
by: Lai, Zhixin, et al.
Published: (2024)
Rigorous Explanations for Tree Ensembles
by: Izza, Yacine, et al.
Published: (2026)
by: Izza, Yacine, et al.
Published: (2026)
A Fused Gromov-Wasserstein Approach to Subgraph Contrastive Learning
by: Sangare, Amadou S., et al.
Published: (2025)
by: Sangare, Amadou S., et al.
Published: (2025)
Fourier Sliced-Wasserstein Embedding for Multisets and Measures
by: Amir, Tal, et al.
Published: (2025)
by: Amir, Tal, et al.
Published: (2025)
Tree-Sliced Wasserstein Distance with Nonlinear Projection
by: Tran, Thanh, et al.
Published: (2025)
by: Tran, Thanh, et al.
Published: (2025)
Distance-Based Tree-Sliced Wasserstein Distance
by: Tran, Hoang V., et al.
Published: (2025)
by: Tran, Hoang V., et al.
Published: (2025)
Bures-Wasserstein Flow Matching for Graph Generation
by: Jiang, Keyue, et al.
Published: (2025)
by: Jiang, Keyue, et al.
Published: (2025)
Graph data augmentation with Gromow-Wasserstein Barycenters
by: Ponti, Andrea
Published: (2024)
by: Ponti, Andrea
Published: (2024)
On the Wasserstein Gradient Flow Interpretation of Drifting Models
by: Gretton, Arthur, et al.
Published: (2026)
by: Gretton, Arthur, et al.
Published: (2026)
Downscaling Extreme Precipitation with Wasserstein Regularized Diffusion
by: Liu, Yuhao, et al.
Published: (2024)
by: Liu, Yuhao, et al.
Published: (2024)
XLand-100B: A Large-Scale Multi-Task Dataset for In-Context Reinforcement Learning
by: Nikulin, Alexander, et al.
Published: (2024)
by: Nikulin, Alexander, et al.
Published: (2024)
Scalable Ensemble Diversification for OOD Generalization and Detection
by: Rubinstein, Alexander, et al.
Published: (2024)
by: Rubinstein, Alexander, et al.
Published: (2024)
Similar Items
-
Normalizing self-supervised learning for provably reliable Change Point Detection
by: Bazarova, Alexandra, et al.
Published: (2024) -
InDiD: Instant Disorder Detection via Representation Learning
by: Romanenkova, Evgenia, et al.
Published: (2021) -
Learning Transactions Representations for Information Management in Banks: Mastering Local, Global, and External Knowledge
by: Bazarova, Alexandra, et al.
Published: (2024) -
DeNOTS: Stable Deep Neural ODEs for Time Series
by: Kuleshov, Ilya, et al.
Published: (2024) -
A theoretical framework for self-supervised contrastive learning for continuous dependent data
by: Marusov, Alexander, et al.
Published: (2025)