:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Zhou, Hang, Wu, Haixu, Shangguan, Haonan, Ma, Yuezhou, Weng, Huikun, Wang, Jianmin, Long, Mingsheng
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2602.04940
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Transolver++: An Accurate Neural Solver for PDEs on Million-Scale Geometries
by: Luo, Huakun, et al.
Published: (2025)

Transolver: A Fast Transformer Solver for PDEs on General Geometries
by: Wu, Haixu, et al.
Published: (2024)

ProPINN: Demystifying Propagation Failures in Physics-Informed Neural Networks
by: Wu, Haixu, et al.
Published: (2025)

PhySense: Sensor Placement Optimization for Accurate Physics Sensing
by: Ma, Yuezhou, et al.
Published: (2025)

Unisolver: PDE-Conditional Transformers Towards Universal Neural PDE Solvers
by: Zhou, Hang, et al.
Published: (2024)

HelmFluid: Learning Helmholtz Dynamics for Interpretable Fluid Prediction
by: Xing, Lanxiang, et al.
Published: (2023)

RoPINN: Region Optimized Physics-Informed Neural Networks
by: Wu, Haixu, et al.
Published: (2024)

Brep2Shape: Boundary and Shape Representation Alignment via Self-Supervised Transformers
by: Sun, Yuanxu, et al.
Published: (2026)

FlashBias: Fast Computation of Attention with Bias
by: Wu, Haixu, et al.
Published: (2025)

Metadata Matters for Time Series: Informative Forecasting with Transformers
by: Dong, Jiaxiang, et al.
Published: (2024)

Exploring Accuracy Law for Deep Time Series Forecasters: An Empirical Study
by: Wang, Yuxuan, et al.
Published: (2025)

Deep Time Series Models: A Comprehensive Survey and Benchmark
by: Wang, Yuxuan, et al.
Published: (2024)

iTransformer: Inverted Transformers Are Effective for Time Series Forecasting
by: Liu, Yong, et al.
Published: (2023)

TimeSiam: A Pre-Training Framework for Siamese Time-Series Modeling
by: Dong, Jiaxiang, et al.
Published: (2024)

GeoPT: Scaling Physics Simulation via Lifted Geometric Pre-Training
by: Wu, Haixu, et al.
Published: (2026)

TimeXer: Empowering Transformers for Time Series Forecasting with Exogenous Variables
by: Wang, Yuxuan, et al.
Published: (2024)

DeepLag: Discovering Deep Lagrangian Dynamics for Intuitive Fluid Prediction
by: Ma, Qilong, et al.
Published: (2024)

Timer-XL: Long-Context Transformers for Unified Time Series Forecasting
by: Liu, Yong, et al.
Published: (2024)

GeoTransolver: Learning Physics on Irregular Domains Using Multi-scale Geometry Aware Physics Attention Transformer
by: Adams, Corey, et al.
Published: (2025)

Timer: Generative Pre-trained Transformers Are Large Time Series Models
by: Liu, Yong, et al.
Published: (2024)

DiTS: Multimodal Diffusion Transformers Are Time Series Forecasters
by: Zhang, Haoran, et al.
Published: (2026)

CompilerDream: Learning a Compiler World Model for General Code Optimization
by: Deng, Chaoyi, et al.
Published: (2024)

Transolver is a Linear Transformer: Revisiting Physics-Attention through the Lens of Linear Attention
by: Hu, Wenjie, et al.
Published: (2025)

Domain Guidance: A Simple Transfer Approach for a Pre-trained Diffusion Model
by: Zhong, Jincheng, et al.
Published: (2025)

Regression Models Meet Foundation Models: A Hybrid-AI Approach to Practical Electricity Price Forecasting
by: Qiu, Yunzhong, et al.
Published: (2026)

AutoTimes: Autoregressive Time Series Forecasters via Large Language Models
by: Liu, Yong, et al.
Published: (2024)

HarmonyDream: Task Harmonization Inside World Models
by: Ma, Haoyu, et al.
Published: (2023)

On the Embedding Collapse when Scaling up Recommendation Models
by: Guo, Xingzhuo, et al.
Published: (2023)

Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution
by: Wang, Xufei, et al.
Published: (2025)

CogDPM: Diffusion Probabilistic Models via Cognitive Predictive Coding
by: Chen, Kaiyuan, et al.
Published: (2024)

Unisoma: A Unified Transformer-based Solver for Multi-Solid Systems
by: Tao, Shilong, et al.
Published: (2025)

Efficient Decoder Scaling Strategy for Neural Routing Solvers
by: Luo, Qing, et al.
Published: (2026)

TimesBERT: A BERT-Style Foundation Model for Time Series Understanding
by: Zhang, Haoran, et al.
Published: (2025)

Learning Nonlinear Responses in PET Bottle Buckling with a Hybrid DeepONet-Transolver Framework
by: Kumar, Varun, et al.
Published: (2025)

Dynamical Diffusion: Learning Temporal Dynamics with Diffusion Models
by: Guo, Xingzhuo, et al.
Published: (2025)

depyf: Open the Opaque Box of PyTorch Compiler for Machine Learning Researchers
by: You, Kaichao, et al.
Published: (2024)

DMSC: Dynamic Multi-Scale Coordination Framework for Time Series Forecasting
by: Yang, Haonan, et al.
Published: (2025)

Vchitect-2.0: Parallel Transformer for Scaling Up Video Diffusion Models
by: Fan, Weichen, et al.
Published: (2025)

Scaling Up Data Parallelism in Decentralized Deep Learning
by: Xie, Bing, et al.
Published: (2025)

INViT: A Generalizable Routing Problem Solver with Invariant Nested View Transformer
by: Fang, Han, et al.
Published: (2024)