:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Bülte, Christopher, Leimenstoll, Lisa, Schienle, Melanie
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2407.08668
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Graph Neural Networks for Enhancing Ensemble Forecasts of Extreme Rainfall
by: Bülte, Christopher, et al.
Published: (2025)

Modeling Nonstationary Extremal Dependence via Deep Spatial Deformations
by: Shao, Xuanjie, et al.
Published: (2025)

Probabilistic intraday electricity price forecasting using generative machine learning
by: Chen, Jieyu, et al.
Published: (2025)

Probabilistic neural operators for functional uncertainty quantification
by: Bülte, Christopher, et al.
Published: (2025)

Improved probabilistic regression using diffusion models
by: Kneissl, Carlo, et al.
Published: (2025)

Uncertainty Quantification for Regression: A Unified Framework based on kernel scores
by: Bülte, Christopher, et al.
Published: (2025)

Uncertainty quantification for data-driven weather models
by: Bülte, Christopher, et al.
Published: (2024)

A Review of Neural Networks in Precipitation Prediction
by: Zeng, Yugong, et al.
Published: (2025)

Towards Location-Specific Precipitation Projections Using Deep Neural Networks
by: Kumar, Bipin, et al.
Published: (2025)

An Axiomatic Assessment of Entropy- and Variance-based Uncertainty Quantification in Regression
by: Bülte, Christopher, et al.
Published: (2025)

Model Determination for High-Dimensional Longitudinal Data with Missing Observations: An Application to Microfinance Data
by: Rüter, Lotta, et al.
Published: (2024)

Canonical Tail Dependence for Soft Extremal Clustering of Multichannel Brain Signals
by: Talento, Mara Sherlin, et al.
Published: (2025)

Bayesian Semi-Parametric Spatial Dispersed Count Model for Precipitation Analysis
by: Nadifar, Mahsa, et al.
Published: (2025)

Simple Macroeconomic Forecast Distributions for the G7 Economies
by: Becker, Friederike, et al.
Published: (2024)

Self-supervised Spatial-Temporal Learner for Precipitation Nowcasting
by: Li, Haotian, et al.
Published: (2024)

Rectifying Distribution Shift in Cascaded Precipitation Nowcasting
by: Ju, Fanbo, et al.
Published: (2025)

Spatial Bayesian Neural Networks
by: Zammit-Mangion, Andrew, et al.
Published: (2023)

Training Robust Graph Neural Networks by Modeling Noise Dependencies
by: In, Yeonjun, et al.
Published: (2025)

On Distributional Dependent Performance of Classical and Neural Routing Solvers
by: Thyssens, Daniela, et al.
Published: (2025)

Predicting the Temperature Dependence of Surfactant CMCs Using Graph Neural Networks
by: Brozos, Christoforos, et al.
Published: (2024)

Performance Heterogeneity in Graph Neural Networks: Lessons for Architecture Design and Preprocessing
by: Fesser, Lukas, et al.
Published: (2025)

Modeling Spatial Extremes using Non-Gaussian Spatial Autoregressive Models via Convolutional Neural Networks
by: Rai, Sweta, et al.
Published: (2025)

Precipitation Nowcasting Using Physics Informed Discriminator Generative Models
by: Yin, Junzhe, et al.
Published: (2024)

MAD-SmaAt-GNet: A Multimodal Advection-Guided Neural Network for Precipitation Nowcasting
by: van Wonderen, Samuel, et al.
Published: (2026)

Empowering Power Outage Prediction with Spatially Aware Hybrid Graph Neural Networks and Contrastive Learning
by: Shen, Xuyang, et al.
Published: (2026)

Visual Spatial Learning: Single-Field Spatial Interpolation Using Convolutional Neural Networks
by: Tinoco, Daniel, et al.
Published: (2026)

Quantum Extremal Learning
by: Varsamopoulos, Savvas, et al.
Published: (2022)

Distributional Regression U-Nets for the Postprocessing of Precipitation Ensemble Forecasts
by: Pic, Romain, et al.
Published: (2024)

Data-Driven and Theory-Guided Pseudo-Spectral Seismic Imaging Using Deep Neural Network Architectures
by: Zerafa, Christopher
Published: (2025)

Hardness of Learning Neural Networks under the Manifold Hypothesis
by: Kiani, Bobak T., et al.
Published: (2024)

Graph Topic Modeling for Documents with Spatial or Covariate Dependencies
by: Jung, Yeo Jin, et al.
Published: (2024)

Inference in Partially Linear Models under Dependent Data with Deep Neural Networks
by: Brown, Chad
Published: (2024)

Spatially Parallel All-optical Neural Networks
by: Qin, Jianwei, et al.
Published: (2025)

A Subsampling Based Neural Network for Spatial Data
by: Thakur, Debjoy
Published: (2024)

Dynamic Localisation of Spatial-Temporal Graph Neural Network
by: Duan, Wenying, et al.
Published: (2025)

The Map Equation Goes Neural: Mapping Network Flows with Graph Neural Networks
by: Blöcker, Christopher, et al.
Published: (2023)

Effective Capacitance Modeling Using Graph Neural Networks
by: Dogan, Eren, et al.
Published: (2025)

Enforcing convex constraints in Graph Neural Networks
by: Rashwan, Ahmed, et al.
Published: (2025)

A Likelihood-Based Generative Approach for Spatially Consistent Precipitation Downscaling
by: González-Abad, Jose
Published: (2024)

Energy-Arena: A Dynamic Benchmark for Operational Energy Forecasting
by: Kleinebrahm, Max, et al.
Published: (2026)