Wenlong Zhang
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  • Experience
  • Publications
    • Intern-S2-Preview: Scientific Agentic Foundation Model
    • SciHazard: A Benchmark for Measuring Scientific Safety Risks with Decomposed Harm Scoring
    • Ideas Have Genomes: Benchmarking Scientific Lineage Reasoning and Lineage-Grounded Idea Generation
    • Scaling the Horizon, Not the Parameters: Reaching Trillion-Parameter Performance with a 35B Agent
    • Agents-K1: Towards Agent-native Knowledge Orchestration
    • SCI-PRM: A Tool Aware Process Reward Model for Scientific Reasoning Verification
    • ResearchClawBench: A Benchmark for End-to-End Autonomous Scientific Research
    • ReCrit: Transition-Aware Reinforcement Learning for Scientific Critic Reasoning
    • Earth-o1: A Grid-free Observation-native Atmospheric World Model
    • Intern-S1-Pro: Scientific Multimodal Foundation Model at Trillion Scale
    • OpenEarth-Agent: From Tool Calling to Tool Creation for Open-Environment Earth Observation
    • FinPercep-RM: A Fine-grained Reward Model and Co-evolutionary Curriculum for RL-based Real-world Super-Resolution
    • InternAgent-1.5: A Unified Agentic Framework for Long-Horizon Autonomous Scientific Discovery
    • Omni-Weather: Unified Multimodal Foundation Model for Weather Generation and Understanding
    • PICABench: How Far Are We from Physically Realistic Image Editing?
    • SciDataCopilot: An Agentic Data Preparation Framework for AGI-driven Scientific Discovery
    • SynWeather: Weather Observation Data Synthesis across Multiple Regions and Variables via a General Diffusion Transformer
    • MSEarth: A Multimodal Scientific Dataset and Benchmark for Phenomena Uncovering in Earth Science
    • DeepResearch Arena: The First Exam of LLMs' Research Abilities via Seminar-Grounded Tasks
    • A Survey of Scientific Large Language Models: From Data Foundations to Agent Frontiers
    • Align-DA: Align Score-based Atmospheric Data Assimilation with Multiple Preferences
    • ATLAS: A High-Difficulty, Multidisciplinary Benchmark for Frontier Scientific Reasoning
    • DAWP: A framework for global observation forecasting via Data Assimilation and Weather Prediction in satellite observation space
    • Decouple to Reconstruct: High Quality UHD Restoration via Active Feature Disentanglement and Reversible Fusion
    • DiffSR: Learning Radar Reflectivity Synthesis via Diffusion Model from Satellite Observations
    • Earth-Agent: Unlocking the Full Landscape of Earth Observation with Agents
    • EarthLink: Interpreting Climate Signals with Self-Evolving AI Agents
    • Eigen-1: Adaptive Multi-Agent Refinement with Monitor-Based RAG for Scientific Reasoning
    • EWE: An Agentic Framework for Extreme Weather Analysis
    • Exploring Representation-Aligned Latent Space for Better Generation
    • Exploring Scalable Unified Modeling for General Low-Level Vision
    • FlowSearch: Advancing deep research with dynamic structured knowledge flow
    • Intern-s1: A scientific multimodal foundation model
    • Large multimodal models evaluation: a survey
    • Latent Harmony: Synergistic Unified UHD Image Restoration via Latent Space Regularization and Controllable Refinement
    • LO-SDA: Latent Optimization for Score-based Atmospheric Data Assimilation
    • Lumina-omnilv: A unified multimodal framework for general low-level vision
    • Manalyzer: End-to-end Automated Meta-analysis with Multi-agent System
    • OmniEarth-Bench: Towards Holistic Evaluation of Earth's Six Spheres and Cross-Spheres Interactions with Multimodal Observational Earth Data
    • PhysUniBench: An Undergraduate-Level Physics Reasoning Benchmark for Multimodal Models
    • Postcast: Generalizable postprocessing for precipitation nowcasting via unsupervised blurriness modeling
    • Probing Scientific General Intelligence of LLMs with Scientist-Aligned Workflows
    • RadarQA: Multi-modal Quality Analysis of Weather Radar Forecasts
    • Scientists' First Exam: Probing Cognitive Abilities of MLLM via Perception, Understanding, and Reasoning
    • SciEvalKit: An Open-source Evaluation Toolkit for Scientific General Intelligence
    • SciReasoner: Laying the Scientific Reasoning Ground Across Disciplines
    • SynCast: Synergizing Contradictions in Precipitation Nowcasting via Diffusion Sequential Preference Optimization
    • The operational medium-range deterministic weather forecasting can be extended beyond a 10-day lead time
    • Understand Before You Generate: Self-Guided Training for Autoregressive Image Generation
    • UniPercept: Towards Unified Perceptual-Level Image Understanding across Aesthetics, Quality, Structure, and Texture
    • VeriGUI: Verifiable Long-Chain GUI Dataset
    • WeatherGFM: Learning A Weather Generalist Foundation Model via In-context Learning
    • A Preliminary Exploration Towards General Image Restoration
    • Generalizing Weather Forecast to Fine-grained Temporal Scales via Physics-AI Hybrid Modeling
    • GRIDS: Grouped Multiple-Degradation Restoration with Image Degradation Similarity
    • Learning A Low-Level Vision Generalist via Visual Task Prompt
    • SEAL: A Framework for Systematic Evaluation of Real-World Super-Resolution
    • Understanding Layer Significance in LLM Alignment
    • UniFashion: A Unified Vision-Language Model for Multimodal Fashion Retrieval and Generation
    • HAT: Hybrid Attention Transformer for Image Restoration
    • Real-World Image Super-Resolution as Multi-Task Learning
    • Recon: Reducing Conflicting Gradients From the Root For Multi-Task Learning
    • Spatial Resolution Matching of Microwave Radiometer Measurements Using Iterative Deconvolution with Close Loop Priors (ICLP)
    • A Closer Look at Blind Super-Resolution: Degradation Models, Baselines, and Performance Upper Bounds
    • Overcoming Catastrophic Forgetting in Incremental Few-Shot Learning by Finding Flat Minima
    • Ranksrgan: Generative adversarial networks with ranker for image super-resolution
    • Radar Cross Section Near-Field to Far-Field Prediction for Isotropic-Point Scattering Target Based on Regression Estimation
    • Ranksrgan: Generative adversarial networks with ranker for image super-resolution
    • Spatial resolution enhancement of satellite microwave radiometer data with deep residual convolutional neural network
    • Spatial resolution matching of microwave radiometer data with convolutional neural network
    • A deconvolution technology of microwave radiometer data using convolutional neural networks
  • Research projects
    • Scientific agents
    • SciPrismax
    • Weather foundation models
  • News
    • Six papers accepted by NeurIPS
    • Scientists' First Exam released
    • WeatherGFM accepted by ICLR 2025
    • DiffSR accepted by ICASSP 2025
    • Papers accepted by EMNLP and NeurIPS
    • Papers accepted by ECCV and ACM MM

A deconvolution technology of microwave radiometer data using convolutional neural networks

Jan 1, 2018·
Weidong Hu
,
Wenlong Zhang
,
Shi Chen
,
Xin Lv
,
Dawei An
,
Leo Ligthart
· 0 min read
Site
Type
Journal article
Publication
Remote Sensing
publications
Last updated on Jan 1, 2018
← Spatial resolution matching of microwave radiometer data with convolutional neural network Jan 1, 2019

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