14 papers
CompilerDream: Learning a Compiler World Model for General Code Optimization
Chaoyi Deng, Jialong Wu, Ningya Feng +2
Effective code optimization in compilers is crucial for computer and software engineering. The success of these optimizations primarily depends on the selection and ordering of the…
Deep Time Series Models: A Comprehensive Survey and Benchmark
Yuxuan Wang, Haixu Wu, Jiaxiang Dong +4
Time series, characterized by a sequence of data points organized in a discrete-time order, are ubiquitous in real-world scenarios. Unlike other data modalities, time series presen…
ProPINN: Demystifying Propagation Failures in Physics-Informed Neural Networks
Haixu Wu, Yuezhou Ma, Hang Zhou +3
Physics-informed neural networks (PINNs) have earned high expectations in solving partial differential equations (PDEs), but their optimization usually faces thorny challenges due…
Domain Guidance: A Simple Transfer Approach for a Pre-trained Diffusion Model
Jincheng Zhong, Xiangcheng Zhang, Jianmin Wang +1
Recent advancements in diffusion models have revolutionized generative modeling. However, the impressive and vivid outputs they produce often come at the cost of significant model…
Dynamical Diffusion: Learning Temporal Dynamics with Diffusion Models
Xingzhuo Guo, Yu Zhang, Baixu Chen +3
Diffusion models have emerged as powerful generative frameworks by progressively adding noise to data through a forward process and then reversing this process to generate realisti…
Timer-XL: Long-Context Transformers for Unified Time Series Forecasting
Yong Liu, Guo Qin, Xiangdong Huang +2
We present Timer-XL, a causal Transformer for unified time series forecasting. To uniformly predict multidimensional time series, we generalize next token prediction, predominantly…