Cover Image

Forecasting Smog Clouds With Deep Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Oldenburg, Valentijn, Cardenas-Cartagena, Juan, Valdenegro-Toro, Matias
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Sanity Checks for Explanation Uncertainty
by: Valdenegro-Toro, Matias, et al.
Published: (2024)

Uncertainty Quantification for Gradient-based Explanations in Neural Networks
by: Mulye, Mihir, et al.
Published: (2024)

Confidence Calibration in Large Language Model-Based Entity Matching
by: Kamsteeg, Iris, et al.
Published: (2025)

Modeling of AUV Dynamics with Limited Resources: Efficient Online Learning Using Uncertainty
by: Tešnar, Michal, et al.
Published: (2025)

Can Bayesian Neural Networks Explicitly Model Input Uncertainty?
by: Valdenegro-Toro, Matias, et al.
Published: (2025)

Uncertainty Quantification for Motor Imagery BCI -- Machine Learning vs. Deep Learning
by: Suurmeijer, Joris, et al.
Published: (2025)

Overconfidence is Key: Verbalized Uncertainty Evaluation in Large Language and Vision-Language Models
by: Groot, Tobias, et al.
Published: (2024)

Informed Learning for Estimating Drought Stress at Fine-Scale Resolution Enables Accurate Yield Prediction
by: Miranda, Miro, et al.
Published: (2025)

Uncertainty in Semantic Language Modeling with PIXELS
by: Radu, Stefania, et al.
Published: (2025)

Deep Gaussian Process Proximal Policy Optimization
by: van der Lende, Matthijs, et al.
Published: (2025)

Unified Uncertainties: Combining Input, Data and Model Uncertainty into a Single Formulation
by: Valdenegro-Toro, Matias, et al.
Published: (2024)

Uncertainty Quantification in Machine Learning for Biosignal Applications -- A Review
by: de Jong, Ivo Pascal, et al.
Published: (2023)

Interpretable Deep Learning for Forecasting Online Advertising Costs: Insights from the Competitive Bidding Landscape
by: Oldenburg, Fynn, et al.
Published: (2023)

Know What You do Not Know: Verbalized Uncertainty Estimation Robustness on Corrupted Images in Vision-Language Models
by: Borszukovszki, Mirko, et al.
Published: (2025)

Terrain Classification Enhanced with Uncertainty for Space Exploration Robots from Proprioceptive Data
by: Álvarez, Mariela De Lucas, et al.
Published: (2024)

Measuring Orthogonality as the Blind-Spot of Uncertainty Disentanglement
by: de Jong, Ivo Pascal, et al.
Published: (2024)

Upside-Down Reinforcement Learning for More Interpretable Optimal Control
by: Cardenas-Cartagena, Juan, et al.
Published: (2024)

The Challenge of Out-Of-Distribution Detection in Motor Imagery BCIs
by: Mulder, Merlijn Quincent, et al.
Published: (2026)

A Neuromorphic Approach to Obstacle Avoidance in Robot Manipulation
by: Abdelrahman, Ahmed Faisal, et al.
Published: (2024)

On the Generalisation of Koopman Representations for Chaotic System Control
by: Hjikakou, Kyriakos, et al.
Published: (2025)

Adaptive Prompt Tuning: Vision Guided Prompt Tuning with Cross-Attention for Fine-Grained Few-Shot Learning
by: Brouwer, Eric, et al.
Published: (2024)

Uncertainty Quantification for cross-subject Motor Imagery classification
by: Manivannan, Prithviraj, et al.
Published: (2024)

The Marine Debris Forward-Looking Sonar Datasets
by: Valdenegro-Toro, Matias, et al.
Published: (2025)

Mapping Transformer Leveraged Embeddings for Cross-Lingual Document Representation
by: Tashu, Tsegaye Misikir, et al.
Published: (2024)

Sparsity-Driven Plasticity in Multi-Task Reinforcement Learning
by: Todorov, Aleksandar, et al.
Published: (2025)

Large-image Object Detection for Fine-grained Recognition of Punches Patterns in Medieval Panel Painting
by: Bruegger, Josh, et al.
Published: (2025)

Navigating the Smog: A Cooperative Multi-Agent RL for Accurate Air Pollution Mapping through Data Assimilation
by: Mokhtari, Ichrak, et al.
Published: (2024)

Transferring BCI models from calibration to control: Observing shifts in EEG features
by: de Jong, Ivo Pascal, et al.
Published: (2024)

Forecast-Then-Optimize Deep Learning Methods
by: Jiang, Jinhang, et al.
Published: (2025)

Deep Subspace Learning for Surface Anomaly Classification Based on 3D Point Cloud Data
by: Cao, Xuanming, et al.
Published: (2025)

Forecasting VIX using Bayesian Deep Learning
by: Hortúa, Héctor J., et al.
Published: (2024)

Online Data Augmentation for Forecasting with Deep Learning
by: Cerqueira, Vitor, et al.
Published: (2024)

Selective Learning for Deep Time Series Forecasting
by: Fu, Yisong, et al.
Published: (2025)

Explore the Ideology of Deep Learning in ENSO Forecasts
by: Gan, Yanhai, et al.
Published: (2026)

On the Measure of a Model: From Intelligence to Generality
by: Dhar, Ruchira, et al.
Published: (2025)

The Dilemma of Uncertainty Estimation for General Purpose AI in the EU AI Act
by: Valdenegro-Toro, Matias, et al.
Published: (2024)

FIDLAR: Forecast-Informed Deep Learning Architecture for Flood Mitigation
by: Shi, Jimeng, et al.
Published: (2024)

Enhancing Exchange Rate Forecasting with Explainable Deep Learning Models
by: Meng, Shuchen, et al.
Published: (2024)

Multiple Yield Curve Modeling and Forecasting using Deep Learning
by: Richman, Ronald, et al.
Published: (2024)

Forecasting with Deep Learning: Beyond Average of Average of Average Performance
by: Cerqueira, Vitor, et al.
Published: (2024)