Cover Image

Bubbleformer: Forecasting Boiling with Transformers

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Hassan, Sheikh Md Shakeel, Zou, Xianwei, Dhruv, Akash, Ganesan, Vishwanath, Chandramowlishwaran, Aparna
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence Computational Engineering, Finance, and Science
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

(HB-ARFM) History-Bootstrapped Flow Matching for Inverse Boiling Reconstruction
by: Zou, Xianwei, et al.
Published: (2026)

Hidformer: Transformer-Style Neural Network in Stock Price Forecasting
by: Szydłowski, Kamil Ł., et al.
Published: (2024)

DoubleAdapt: A Meta-learning Approach to Incremental Learning for Stock Trend Forecasting
by: Zhao, Lifan, et al.
Published: (2023)

Forecasting VIX using interpretable Kolmogorov-Arnold networks
by: Cho, So-Yoon, et al.
Published: (2025)

CaFA: Global Weather Forecasting with Factorized Attention on Sphere
by: Li, Zijie, et al.
Published: (2024)

FHRFormer: A Self-Supervised Masked Transformer Framework for Fetal Heart Rate Time-Series Inpainting and Forecasting
by: Engan, Kjersti, et al.
Published: (2026)

CauSTream: Causal Spatio-Temporal Representation Learning for Streamflow Forecasting
by: Wan, Shu, et al.
Published: (2025)

GIFT: Bootstrapping Image-to-CAD Program Synthesis via Geometric Feedback
by: Giannone, Giorgio, et al.
Published: (2026)

FLAG: Financial Long Document Classification via AMR-based GNN
by: Xia, Bolun "Namir", et al.
Published: (2024)

Proactive Model Adaptation Against Concept Drift for Online Time Series Forecasting
by: Zhao, Lifan, et al.
Published: (2024)

Trade When Opportunity Comes: Price Movement Forecasting via Locality-Aware Attention and Iterative Refinement Labeling
by: Zeng, Liang, et al.
Published: (2021)

Ada-MoGE: Adaptive Mixture of Gaussian Expert Model for Time Series Forecasting
by: Ni, Zhenliang, et al.
Published: (2025)

Transformers with Attentive Federated Aggregation for Time Series Stock Forecasting
by: Thwal, Chu Myaet, et al.
Published: (2024)

Sparse Latent Factor Forecaster (SLFF) with Iterative Inference for Transparent Multi-Horizon Commodity Futures Prediction
by: Gupta, Abhijit
Published: (2025)

FETS Benchmark: Foundation Models Outperform Dataset-specific Machine Learning in Energy Time Series Forecasting
by: Obermeier, Marco, et al.
Published: (2026)

Predicting Stock Movement with BERTweet and Transformers
by: Albada, Michael Charles, et al.
Published: (2025)

The Rise of AI Teammates in Software Engineering (SE) 3.0: How Autonomous Coding Agents Are Reshaping Software Engineering
by: Li, Hao, et al.
Published: (2025)

Multistep Brent Oil Price Forecasting with a Multi-Aspect Meta-heuristic Optimization and Ensemble Deep Learning Model
by: Alruqimi, Mohammed, et al.
Published: (2024)

Learning Flexible Body Collision Dynamics with Hierarchical Contact Mesh Transformer
by: Yu, Youn-Yeol, et al.
Published: (2023)

Graph Transformers for inverse physics: reconstructing flows around arbitrary 2D airfoils
by: Duthé, Gregory, et al.
Published: (2025)

Physics-Informed Teacher-Student Ensemble Learning for Traffic State Estimation with a Varying Speed Limit Scenario
by: Huang, Archie J., et al.
Published: (2026)

R&D-Agent-Quant: A Multi-Agent Framework for Data-Centric Factors and Model Joint Optimization
by: Li, Yuante, et al.
Published: (2025)

MANA-Net: Mitigating Aggregated Sentiment Homogenization with News Weighting for Enhanced Market Prediction
by: Wang, Mengyu, et al.
Published: (2024)

CatMemo at the FinLLM Challenge Task: Fine-Tuning Large Language Models using Data Fusion in Financial Applications
by: Cao, Yupeng, et al.
Published: (2024)

Financial Assets Dependency Prediction Utilizing Spatiotemporal Patterns
by: Zhu, Haoren, et al.
Published: (2024)

FHRFormer: A Self-supervised Transformer Approach for Fetal Heart Rate Inpainting and Forecasting
by: Engan, Kjersti, et al.
Published: (2025)

PHAST: Port-Hamiltonian Architecture for Structured Temporal Dynamics Forecasting
by: Bhardwaj, Shubham, et al.
Published: (2026)

Physics-Informed Distillation of Diffusion Models for PDE-Constrained Generation
by: Zhang, Yi, et al.
Published: (2025)

DeepSupp: Attention-Driven Correlation Pattern Analysis for Dynamic Time Series Support and Resistance Levels Identification
by: Kriuk, Boris, et al.
Published: (2025)

Deep Learning Models Meet Financial Data Modalities
by: Khubiev, Kasymkhan, et al.
Published: (2025)

Off-the-Shelf Neural Network Architectures for Forex Time Series Prediction come at a Cost
by: Zafeiriou, Theodoros, et al.
Published: (2024)

StockTime: A Time Series Specialized Large Language Model Architecture for Stock Price Prediction
by: Wang, Shengkun, et al.
Published: (2024)

Temporal distribution of clusters of investors and their application in prediction with expert advice
by: Wisniewski, Wojciech, et al.
Published: (2024)

ARTEMIS: A Neuro Symbolic Framework for Economically Constrained Market Dynamics
by: Ray, Rahul D
Published: (2026)

Bitcoin Price Prediction using Machine Learning and Combinatorial Fusion Analysis
by: Wu, Yuanhong, et al.
Published: (2026)

Retrosynthesis Planning via Worst-path Policy Optimisation in Tree-structured MDPs
by: Wang, Mianchu, et al.
Published: (2025)

An Advanced Convolutional Neural Network for Bearing Fault Diagnosis under Limited Data
by: Sun, Shengke, et al.
Published: (2025)

BikeBench: A Bicycle Design Benchmark for Generative Models with Objectives and Constraints
by: Regenwetter, Lyle, et al.
Published: (2025)

Lean 5.0: A Predictive, Human-AI, and Ethically Grounded Paradigm for Construction Management
by: Khoshkonesh, Atena, et al.
Published: (2025)

AI Agents in Engineering Design: A Multi-Agent Framework for Aesthetic and Aerodynamic Car Design
by: Elrefaie, Mohamed, et al.
Published: (2025)