1 citations · 4 across the 27 of their papers we have counts for
32 papers
Earth System World Model for What-If Simulations: A Case Study for Terrestrial Ecosystems
Zhihao Wang, Ruichen Wang, Ruohan Li +6
Machine learning emulators have become essential for accelerating expensive Earth-system simulations, but most existing approaches remain passive forecasters: they reproduce simula…
Quantifying Event Impacts on Time Series via Multiscale Contrastive Learning
Yiming Sun, Shengyu Chen, Zhengzhang Chen +3
Shocks that spread through the web, such as cybersecurity breach disclosures, can abruptly disrupt financial time series and cause substantial abnormal losses. While these events a…
PIER: Physics-Informed Environmental Retrieval for Time-Series Modeling
Shiyuan Luo, Runlong Yu, Chonghao Qiu +6
Accurate modeling of environmental systems is fundamental to scientific understanding and decision-making, yet remains challenging because observations are limited and physical dyn…
Physics-Preserving Latent Compression for Zero-Shot Resolution Transfer in 3D Turbulence
Yilong Dai, Yiming Sun, Yiheng Chen +4
High-resolution turbulence modeling is essential for scientific computing, but remains constrained by the cost of direct numerical simulation and the scarcity of full-resolution da…
Flow Learners for PDEs: Toward a Physics-to-Physics Paradigm for Scientific Computing
Yilong Dai, Shengyu Chen, Xiaowei Jia +1
Partial differential equations (PDEs) govern nearly every physical process in science and engineering, but solving them at scale remains prohibitively expensive. Generative AI has…
Beyond Visual Fidelity: Benchmarking Super-Resolution Models for Large-Scale Remote Sensing Imagery via Downstream Task Integration
Zhili Li, Kangyang Chai, Zhihao Wang +6
Super-resolution (SR) techniques have made major advances in reconstructing high-resolution images from low-resolution inputs. The increased resolution provides visual enhancement…
CHAM-net: A Contrastive Hierarchical Adaptive Meta-network for Robust Global Methane Flux Prediction
Rongchao Dong, Yiming Sun, Shuo Chen +4
Methane is a potent greenhouse gas that significantly contributes to global warming. However, accurately estimating global methane emissions and consumption remains challenging due…
Retrieval-Augmented Multi-scale Framework for County-Level Crop Yield Prediction Across Large Regions
Yiming Sun, Qi Cheng, Licheng Liu +3
This paper proposes a new method for crop yield prediction, which is essential for developing management strategies, informing insurance assessments, and ensuring long-term food se…
Role-Aware Conditional Inference for Spatiotemporal Ecosystem Carbon Flux Prediction
Yiming Sun, Runlong Yu, Rongchao Dong +6
Accurate prediction of terrestrial ecosystem carbon fluxes (e.g., CO, GPP, and CH) is essential for understanding the global carbon cycle and managing its impacts. However,…
Learning PDE Solvers with Physics and Data: A Unifying View of Physics-Informed Neural Networks and Neural Operators
Yilong Dai, Shengyu Chen, Ziyi Wang +4
Partial differential equations (PDEs) are central to scientific modeling. Modern workflows increasingly rely on learning-based components to support model reuse, inference, and int…
AgroFlux: A Spatial-Temporal Benchmark for Carbon and Nitrogen Flux Prediction in Agricultural Ecosystems
Qi Cheng, Licheng Liu, Yao Zhang +3
Agroecosystem, which heavily influenced by human actions and accounts for a quarter of global greenhouse gas emissions (GHGs), plays a crucial role in mitigating global climate cha…
GREAT: Generalizable Representation Enhancement via Auxiliary Transformations for Zero-Shot Environmental Prediction
Shiyuan Luo, Chonghao Qiu, Runlong Yu +2
Environmental modeling faces critical challenges in predicting ecosystem dynamics across unmonitored regions due to limited and geographically imbalanced observation data. This cha…
Geo-Aware Models for Stream Temperature Prediction across Different Spatial Regions and Scales
Shiyuan Luo, Runlong Yu, Shengyu Chen +4
Understanding environmental ecosystems is vital for the sustainable management of our planet. However,existing physics-based and data-driven models often fail to generalize to vary…
Truth Without Comprehension: A BlueSky Agenda for Steering the Fourth Mathematical Crisis
Runlong Yu, Xiaowei Jia
Machine-generated proofs are poised to reach large-scale, human-unreadable artifacts. They foreshadow what we call the Fourth Mathematical Crisis. This crisis crystallizes around t…
Learning to Retrieve for Environmental Knowledge Discovery: An Augmentation-Adaptive Self-Supervised Learning Framework
Shiyuan Luo, Runlong Yu, Chonghao Qiu +5
The discovery of environmental knowledge depends on labeled task-specific data, but is often constrained by the high cost of data collection. Existing machine learning approaches u…
RAG for Geoscience: What We Expect, Gaps and Opportunities
Runlong Yu, Shiyuan Luo, Rahul Ghosh +3
Retrieval-Augmented Generation (RAG) enhances language models by combining retrieval with generation. However, its current workflow remains largely text-centric, limiting its appli…
From Pixels to Places: A Systematic Benchmark for Evaluating Image Geolocalization Ability in Large Language Models
Lingyao Li, Runlong Yu, Qikai Hu +4
Image geolocalization, the task of identifying the geographic location depicted in an image, is important for applications in crisis response, digital forensics, and location-based…
LLM-based Evaluation Policy Extraction for Ecological Modeling
Qi Cheng, Licheng Liu, Qing Zhu +4
Evaluating ecological time series is critical for benchmarking model performance in many important applications, including predicting greenhouse gas fluxes, capturing carbon-nitrog…
Knowledge Guided Encoder-Decoder Framework: Integrating Multiple Physical Models for Agricultural Ecosystem Modeling
Qi Cheng, Licheng Liu, Yao Zhang +5
Agricultural monitoring is critical for ensuring food security, maintaining sustainable farming practices, informing policies on mitigating food shortage, and managing greenhouse g…
Multi-Scale Graph Learning for Anti-Sparse Downscaling
Yingda Fan, Runlong Yu, Janet R. Barclay +4
Water temperature can vary substantially even across short distances within the same sub-watershed. Accurate prediction of stream water temperature at fine spatial resolutions (i.e…
X-MethaneWet: A Cross-scale Global Wetland Methane Emission Benchmark Dataset for Advancing Science Discovery with AI
Yiming Sun, Shuo Chen, Shengyu Chen +9
Methane (CH) is the second most powerful greenhouse gas after carbon dioxide and plays a crucial role in climate change due to its high global warming potential. Accurately mod…
Foundation Models for Environmental Science: A Survey of Emerging Frontiers
Runlong Yu, Shengyu Chen, Yiqun Xie +3
Modeling environmental ecosystems is essential for effective resource management, sustainable development, and understanding complex ecological processes. However, traditional data…
A Survey of Foundation Models for Environmental Science
Runlong Yu, Shengyu Chen, Yiqun Xie +1
Modeling environmental ecosystems is essential for effective resource management, sustainable development, and understanding complex ecological processes. However, traditional meth…
Physics-Guided Foundation Model for Scientific Discovery: An Application to Aquatic Science
Runlong Yu, Chonghao Qiu, Robert Ladwig +3
Physics-guided machine learning (PGML) has become a prevalent approach in studying scientific systems due to its ability to integrate scientific theories for enhancing machine lear…