MVeLMA: Multimodal Vegetation Loss Modeling Architecture for Predicting Post-fire Vegetation Loss
Fuente:
arXiv
Guardado en:
| Autores principales: | Ravi, Meenu, Sarkar, Shailik, Sun, Yanshen, Singh, Vaishnavi, Lu, Chang-Tien |
|---|---|
| Formato: | Preprint |
| Publicado: |
2025
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
StockTime: A Time Series Specialized Large Language Model Architecture for Stock Price Prediction
por: Wang, Shengkun, et al.
Publicado: (2024)
por: Wang, Shengkun, et al.
Publicado: (2024)
Downscaling Precipitation with Bias-informed Conditional Diffusion Model
por: Lyu, Ran, et al.
Publicado: (2024)
por: Lyu, Ran, et al.
Publicado: (2024)
Loss-Controlling Calibration for Predictive Models
por: Wang, Di, et al.
Publicado: (2023)
por: Wang, Di, et al.
Publicado: (2023)
Prediction Loss Guided Decision-Focused Learning
por: Jeon, Haeun, et al.
Publicado: (2025)
por: Jeon, Haeun, et al.
Publicado: (2025)
Conformal Loss-Controlling Prediction
por: Wang, Di, et al.
Publicado: (2023)
por: Wang, Di, et al.
Publicado: (2023)
Global Vegetation Modeling with Pre-Trained Weather Transformers
por: Janetzky, Pascal, et al.
Publicado: (2024)
por: Janetzky, Pascal, et al.
Publicado: (2024)
Density-Ratio Losses for Post-Hoc Learning to Defer
por: Soen, Alexander, et al.
Publicado: (2026)
por: Soen, Alexander, et al.
Publicado: (2026)
Semantic Loss Functions for Neuro-Symbolic Structured Prediction
por: Ahmed, Kareem, et al.
Publicado: (2024)
por: Ahmed, Kareem, et al.
Publicado: (2024)
Extreme-value forest fire prediction A study of the Loss Function in an Ordinality Scheme
por: Caron, Nicolas, et al.
Publicado: (2026)
por: Caron, Nicolas, et al.
Publicado: (2026)
Deep Metric Loss for Multimodal Learning
por: Moon, Sehwan, et al.
Publicado: (2023)
por: Moon, Sehwan, et al.
Publicado: (2023)
Loss-to-Loss Prediction: Scaling Laws for All Datasets
por: Brandfonbrener, David, et al.
Publicado: (2024)
por: Brandfonbrener, David, et al.
Publicado: (2024)
Loss Functions for Predictor-based Neural Architecture Search
por: Ji, Han, et al.
Publicado: (2025)
por: Ji, Han, et al.
Publicado: (2025)
Learning Differentiable Surrogate Losses for Structured Prediction
por: Yang, Junjie, et al.
Publicado: (2024)
por: Yang, Junjie, et al.
Publicado: (2024)
Predicting Large Model Test Losses with a Noisy Quadratic System
por: Li, Chuning, et al.
Publicado: (2026)
por: Li, Chuning, et al.
Publicado: (2026)
Manifold Metric: A Loss Landscape Approach for Predicting Model Performance
por: Malviya, Pranshu, et al.
Publicado: (2024)
por: Malviya, Pranshu, et al.
Publicado: (2024)
Analysis of Using Sigmoid Loss for Contrastive Learning
por: Lee, Chungpa, et al.
Publicado: (2024)
por: Lee, Chungpa, et al.
Publicado: (2024)
Online Structured Prediction with Fenchel--Young Losses and Improved Surrogate Regret for Online Multiclass Classification with Logistic Loss
por: Sakaue, Shinsaku, et al.
Publicado: (2024)
por: Sakaue, Shinsaku, et al.
Publicado: (2024)
Panprediction: Optimal Predictions for Any Downstream Task and Loss
por: Balakrishnan, Sivaraman, et al.
Publicado: (2025)
por: Balakrishnan, Sivaraman, et al.
Publicado: (2025)
Non-Stationary Online Structured Prediction with Surrogate Losses
por: Sakaue, Shinsaku, et al.
Publicado: (2025)
por: Sakaue, Shinsaku, et al.
Publicado: (2025)
AnyLoss: Transforming Classification Metrics into Loss Functions
por: Han, Doheon, et al.
Publicado: (2024)
por: Han, Doheon, et al.
Publicado: (2024)
Lai Loss: A Novel Loss for Gradient Control
por: Lai, YuFei
Publicado: (2024)
por: Lai, YuFei
Publicado: (2024)
In Search for Architectures and Loss Functions in Multi-Objective Reinforcement Learning
por: Terekhov, Mikhail, et al.
Publicado: (2024)
por: Terekhov, Mikhail, et al.
Publicado: (2024)
Towards Robust Few-Shot Text Classification Using Transformer Architectures and Dual Loss Strategies
por: Han, Xu, et al.
Publicado: (2025)
por: Han, Xu, et al.
Publicado: (2025)
Molecular Odor Prediction with Harmonic Modulated Feature Mapping and Chemically-Informed Loss
por: Xie, HongXin, et al.
Publicado: (2025)
por: Xie, HongXin, et al.
Publicado: (2025)
Model Merging on Loss Landscape: A Geometry Perspective
por: Lu, Juanwu, et al.
Publicado: (2026)
por: Lu, Juanwu, et al.
Publicado: (2026)
Online Algorithm for Aggregating Experts' Predictions with Unbounded Quadratic Loss
por: Korotin, Alexander, et al.
Publicado: (2025)
por: Korotin, Alexander, et al.
Publicado: (2025)
Enhancing Joint Motion Prediction for Individuals with Limb Loss Through Model Reprogramming
por: Dey, Sharmita, et al.
Publicado: (2024)
por: Dey, Sharmita, et al.
Publicado: (2024)
Distributional Reinforcement Learning with Regularized Wasserstein Loss
por: Sun, Ke, et al.
Publicado: (2022)
por: Sun, Ke, et al.
Publicado: (2022)
Harmonic Loss Trains Interpretable AI Models
por: Baek, David D., et al.
Publicado: (2025)
por: Baek, David D., et al.
Publicado: (2025)
$p$SVM: Soft-margin SVMs with $p$-norm Hinge Loss
por: Sun, Haoxiang
Publicado: (2024)
por: Sun, Haoxiang
Publicado: (2024)
Learning with Fitzpatrick Losses
por: Rakotomandimby, Seta, et al.
Publicado: (2024)
por: Rakotomandimby, Seta, et al.
Publicado: (2024)
Distributional Adversarial Loss
por: Ahmadi, Saba, et al.
Publicado: (2024)
por: Ahmadi, Saba, et al.
Publicado: (2024)
Stable Coresets via Posterior Sampling: Aligning Induced and Full Loss Landscapes
por: Chang, Wei-Kai, et al.
Publicado: (2025)
por: Chang, Wei-Kai, et al.
Publicado: (2025)
RI-Loss: A Learnable Residual-Informed Loss for Time Series Forecasting
por: Wang, Jieting, et al.
Publicado: (2025)
por: Wang, Jieting, et al.
Publicado: (2025)
LossLens: Diagnostics for Machine Learning through Loss Landscape Visual Analytics
por: Xie, Tiankai, et al.
Publicado: (2024)
por: Xie, Tiankai, et al.
Publicado: (2024)
A Unified Noise-Curvature View of Loss of Trainability
por: Baveja, Gunbir Singh, et al.
Publicado: (2025)
por: Baveja, Gunbir Singh, et al.
Publicado: (2025)
EnsLoss: Stochastic Calibrated Loss Ensembles for Preventing Overfitting in Classification
por: Dai, Ben
Publicado: (2024)
por: Dai, Ben
Publicado: (2024)
Patch-wise Structural Loss for Time Series Forecasting
por: Kudrat, Dilfira, et al.
Publicado: (2025)
por: Kudrat, Dilfira, et al.
Publicado: (2025)
A Pseudo-Semantic Loss for Autoregressive Models with Logical Constraints
por: Ahmed, Kareem, et al.
Publicado: (2023)
por: Ahmed, Kareem, et al.
Publicado: (2023)
Challenges in Training PINNs: A Loss Landscape Perspective
por: Rathore, Pratik, et al.
Publicado: (2024)
por: Rathore, Pratik, et al.
Publicado: (2024)
Ejemplares similares
-
StockTime: A Time Series Specialized Large Language Model Architecture for Stock Price Prediction
por: Wang, Shengkun, et al.
Publicado: (2024) -
Downscaling Precipitation with Bias-informed Conditional Diffusion Model
por: Lyu, Ran, et al.
Publicado: (2024) -
Loss-Controlling Calibration for Predictive Models
por: Wang, Di, et al.
Publicado: (2023) -
Prediction Loss Guided Decision-Focused Learning
por: Jeon, Haeun, et al.
Publicado: (2025) -
Conformal Loss-Controlling Prediction
por: Wang, Di, et al.
Publicado: (2023)