Haixu Wu
20 papers · 2021–2025 · 4 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
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(19)
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(5)
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(5)
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time series forecasting
(6)
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(3)
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(2)
transformer
(2)
linear complexity
(2)
time series
(2)
long-term forecasting
(2)
motion prediction
(2)
partial differential equation
(2)
time series classification
(2)
multivariate time series
(2)
linear attention
(2)
policy optimization
(1)
self-supervised learning
(1)
video prediction
(1)
self-attention mechanism
(1)
time series anomaly detection
(1)
density estimation
(1)
Papers
Transolver++: An Accurate Neural Solver for PDEs on Million-Scale Geometries
ICML 2025
Unisolver: PDE-Conditional Transformers Towards Universal Neural PDE Solvers
ICML 2025
DeepLag: Discovering Deep Lagrangian Dynamics for Intuitive Fluid Prediction
NeurIPS 2024
HelmFluid: Learning Helmholtz Dynamics for Interpretable Fluid Prediction
ICML 2024
iTransformer: Inverted Transformers Are Effective for Time Series Forecasting
ICLR 2024
Mobile Attention: Mobile-Friendly Linear-Attention for Vision Transformers
ICML 2024
RoPINN: Region Optimized Physics-Informed Neural Networks
NeurIPS 2024
TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting
ICLR 2024
TimeSiam: A Pre-Training Framework for Siamese Time-Series Modeling
ICML 2024
TimeXer: Empowering Transformers for Time Series Forecasting with Exogenous Variables
NeurIPS 2024
Transolver: A Fast Transformer Solver for PDEs on General Geometries
ICML 2024
SimMTM: A Simple Pre-Training Framework for Masked Time-Series Modeling
NeurIPS 2023
Solving High-Dimensional PDEs with Latent Spectral Models
ICML 2023
TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis
ICLR 2023
Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy
ICLR 2022
Flowformer: Linearizing Transformers with Conservation Flows
ICML 2022
Non-stationary Transformers: Exploring the Stationarity in Time Series Forecasting
NeurIPS 2022
Supported Policy Optimization for Offline Reinforcement Learning
NeurIPS 2022
Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting
NeurIPS 2021
MotionRNN: A Flexible Model for Video Prediction With Spacetime-Varying Motions
CVPR 2021