:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Author:	Dayan, Baljinnyam
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence
Online Access:	https://arxiv.org/abs/2603.22331
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Characterizing and Predicting Wildfire Evacuation Behavior: A Dual-Stage ML Approach
by: Polock, Sazzad Bin Bashar, et al.
Published: (2026)

Lung Disease Detection with Vision Transformers: A Comparative Study of Machine Learning Methods
by: Dayan, Baljinnyam
Published: (2024)

From Perceptions to Decisions: Wildfire Evacuation Decision Prediction with Behavioral Theory-informed LLMs
by: Chen, Ruxiao, et al.
Published: (2025)

Selective Conformal Risk Control
by: Xu, Yunpeng, et al.
Published: (2025)

GREAT-EER: Graph Edge Attention Network for Emergency Evacuation Responses
by: Lischka, Attila, et al.
Published: (2026)

Automatically Adaptive Conformal Risk Control
by: Blot, Vincent, et al.
Published: (2024)

Explainable Global Wildfire Prediction Models using Graph Neural Networks
by: Chen, Dayou, et al.
Published: (2024)

Reinforcement Learning-Guided Dynamic Multi-Graph Fusion for Evacuation Traffic Prediction
by: Rafi, Md Nafees Fuad, et al.
Published: (2026)

Comparing Task-Agnostic Embedding Models for Tabular Data
by: Hoppe, Frederik, et al.
Published: (2025)

Synthetic Tabular Data Generation for Class Imbalance and Fairness: A Comparative Study
by: Panagiotou, Emmanouil, et al.
Published: (2024)

Conformal Risk Control
by: Angelopoulos, Anastasios N., et al.
Published: (2022)

Causal Graph Neural Networks for Wildfire Danger Prediction
by: Zhao, Shan, et al.
Published: (2024)

Proof of Concept: Multi-Target Wildfire Risk Prediction and Large Language Model Synthesis
by: Caron, Nicolas, et al.
Published: (2026)

Action-Conditioned Risk Gating for Safety-Critical Control under Partial Observability
by: Liu, Yushen, et al.
Published: (2026)

JaxWildfire: A GPU-Accelerated Wildfire Simulator for Reinforcement Learning
by: Çakır, Ufuk, et al.
Published: (2025)

Conformal Thinking: Risk Control for Reasoning on a Compute Budget
by: Wang, Xi, et al.
Published: (2026)

Conformal Safety Monitoring for Flight Testing: A Case Study in Data-Driven Safety Learning
by: Feldman, Aaron O., et al.
Published: (2025)

Advancing Wildfire Risk Prediction via Morphology-Aware Curriculum Contrastive Learning
by: Scudo, Fabrizio Lo, et al.
Published: (2025)

CORA: Conformal Risk-Controlled Agents for Safeguarded Mobile GUI Automation
by: Feng, Yushi, et al.
Published: (2026)

Interpretable Graph Neural Networks for Tabular Data
by: Alkhatib, Amr, et al.
Published: (2023)

A Comparative Study of Open-Source Libraries for Synthetic Tabular Data Generation: SDV vs. SynthCity
by: Del Gobbo, Cristian
Published: (2025)

Learning from Risk: LLM-Guided Generation of Safety-Critical Scenarios with Prior Knowledge
by: Wang, Yuhang, et al.
Published: (2025)

Conformal Selective Acting: Anytime-Valid Risk Control for RLVR-Trained LLMs
by: Khosravi, Hamed, et al.
Published: (2026)

Statistically Assuring Safety of Control Systems using Ensembles of Safety Filters and Conformal Prediction
by: Tabbara, Ihab, et al.
Published: (2025)

Data Presentation Over Architecture: Resampling Strategies for Credit Risk Prediction with Tabular Foundation Models
by: Tanna, Aditya, et al.
Published: (2026)

Robust Tabular Foundation Models
by: Peroni, Matthew, et al.
Published: (2025)

Enhancing Trustworthiness of Graph Neural Networks with Rank-Based Conformal Training
by: Wang, Ting, et al.
Published: (2025)

Fusing Driver Perceived and Physical Risk for Safety Critical Scenario Screening in Autonomous Driving
by: Xiong, Chen, et al.
Published: (2026)

TabularQGAN: A Quantum Generative Model for Tabular Data
by: Bhardwaj, Pallavi, et al.
Published: (2025)

OmniTabBench: Mapping the Empirical Frontiers of GBDTs, Neural Networks, and Foundation Models for Tabular Data at Scale
by: Jiang, Dihong, et al.
Published: (2026)

A Benchmarking Study of Kolmogorov-Arnold Networks on Tabular Data
by: Poeta, Eleonora, et al.
Published: (2024)

Graph Neural Network contextual embedding for Deep Learning on Tabular Data
by: Villaizán-Vallelado, Mario, et al.
Published: (2023)

Automated Model Selection for Tabular Data
by: Amballa, Avinash, et al.
Published: (2024)

Generalization and Informativeness of Weighted Conformal Risk Control Under Covariate Shift
by: Zecchin, Matteo, et al.
Published: (2025)

Critical Challenges and Guidelines in Evaluating Synthetic Tabular Data: A Systematic Review
by: Nafis, Nazia, et al.
Published: (2025)

Does Your Wildfire Prediction Model Actually Work, or Just Score Well?
by: Xu, Yangshuang, et al.
Published: (2026)

Unifying Goal-Conditioned RL and Unsupervised Skill Learning via Control-Maximization
by: Modirshanechi, Alireza, et al.
Published: (2026)

Similarity-Based Self-Construct Graph Model for Predicting Patient Criticalness Using Graph Neural Networks and EHR Data
by: Sahu, Mukesh Kumar, et al.
Published: (2025)

Probabilistic Constraint for Safety-Critical Reinforcement Learning
by: Chen, Weiqin, et al.
Published: (2023)

Scaling Graph Transformers: A Comparative Study of Sparse and Dense Attention
by: Dimitrov, Leon
Published: (2025)