collaborators

6 papers

cs.LG2026

Tyche: One Step Flow for Efficient Probabilistic Weather Forecasting

Fan Xu, Yuan Gao, Kun Wang +4

Probabilistic weather forecasting requires not only accurate trajectories, but calibrated distributions over plausible atmospheric futures. Recent data-driven systems have achieved…

physics.geo-ph2025

DispFormer: A Pretrained Transformer Incorporating Physical Constraints for Dispersion Curve Inversion

Feng Liu, Bao Deng, Rui Su +2

Surface wave dispersion curve inversion is crucial for estimating subsurface shear-wave velocity (vs), yet traditional methods often face challenges related to computational cost,…

physics.geo-ph2025

OpenSWI: A Massive-Scale Benchmark Dataset for Surface Wave Dispersion Curve Inversion

Feng Liu, Sijie Zhao, Xinyu Gu +8

Surface wave dispersion curve inversion plays a critical role in both shallow resource exploration and deep geological studies, yet it remains hindered by sensitivity to initial mo…

cs.LG2025

SeisMoLLM: Advancing Seismic Monitoring via Cross-modal Transfer with Pre-trained Large Language Model

Xinghao Wang, Feng Liu, Rui Su +5

Recent advances in deep learning have revolutionized seismic monitoring, yet developing a foundation model that performs well across multiple complex tasks remains challenging, par…

physics.geo-ph2025

Deep Reparameterization for Full Waveform Inversion: Architecture Benchmarking, Robust Inversion, and Multiphysics Extension

Feng Liu, Yaxing Li, Rui Su +2

Full waveform inversion (FWI) is a high-resolution subsurface imaging technique, but its effectiveness is limited by challenges such as noise contamination, sparse acquisition, and…

cs.MA2025

Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization

Ying Zhu, Heng Zhou, Rui Su +2

Recently, many approaches, such as Chain-of-Thought (CoT) prompting and Multi-Agent Debate (MAD), have been proposed to further enrich Large Language Models' (LLMs) complex problem…