Rose Yu
- Forecasting the future of artificial intelligence with machine learning-based link prediction in an exponentially growing knowledge network
2022/09/23 by Mario Krenn, Lorenzo Buffoni, Bruno Coutinho +15 · 4 voices · 9 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · Physics and Astronomy · #Advanced Graph Neural Networks #Bioinformatics and Genomic Networks #Complex Network Analysis Techniques #cs.AI #cs.LG
- Long-term Forecasting with TiDE: Time-series Dense Encoder
2023/04/17 by Abhimanyu Das, Weihao Kong, Das, Abhimanyu +9 · 52 citations
Computer Science · Physics and Astronomy · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks #Neural Networks and Applications #Time Series Analysis and Forecasting
- Physics-informed machine learning: case studies for weather and climate modelling
2021/02/15 by Karthik Kashinath, Mohamed Elhafiz Mustafa, Adrian Albert +18 · 21 citations
Earth and Planetary Sciences · Environmental Science · Physics and Astronomy · #Climate variability and models #Meteorological Phenomena and Simulations #Model Reduction and Neural Networks
- Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems
2023/07/17 by Xuan Zhang, Limei Wang, Zhang, Xuan +123 · 1 voice · 22 citations
#cs.LG #physics.comp-ph
- Incorporating Symmetry into Deep Dynamics Models for Improved Generalization
2020/02/08 by Rui Wang, Robin Walters, Wang, Rui +3 · 15 citations
Computer Science · Physics and Astronomy · #Computational Physics and Python Applications #FOS: Computer and information sciences #FOS: Mathematics #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks #Representation Theory (math.RT)
- Deep Imitation Learning for Bimanual Robotic Manipulation
2020/10/11 by Fan Xie, Alexander Chowdhury, Xie, Fan +9 · 12 citations
Engineering · Computer Science · #Robot Manipulation and Learning #Human Pose and Action Recognition #Multimodal Machine Learning Applications
- Approximately Equivariant Networks for Imperfectly Symmetric Dynamics
2022/01/28 by Rui Wang, Robin Walters, Wang, Rui +3 · 11 citations
Computer Science · Physics and Astronomy · #Computational Physics and Python Applications #FOS: Computer and information sciences #Machine Learning (cs.LG) #Model Reduction and Neural Networks #Time Series Analysis and Forecasting
- On the Connection Between MPNN and Graph Transformer
2023/01/27 by Cai Chen, Chen Cai, Truong Son Hy +6 · 1 voice · 9 citations
Computer Science · #Advanced Graph Neural Networks #Graph Theory and Algorithms #Recommender Systems and Techniques #cs.LG
- Can LLM feedback enhance review quality? A randomized study of 20K reviews at ICLR 2025
2025/04/13 by Nitya Thakkar, Mert Yuksekgonul, Thakkar, Nitya +16 · 3 voices · 15 citations
Social Sciences · #Delphi Technique in Research
- Automatic Symmetry Discovery with Lie Algebra Convolutional Network
2021/09/15 by Nima Dehmamy, Robin Walters, Dehmamy, Nima +7 · 7 citations
Computer Science · Biochemistry, Genetics and Molecular Biology · #Neural Networks and Applications #Protein Structure and Dynamics #Bioinformatics and Genomic Networks
- Generative Adversarial Symmetry Discovery
2023/02/01 by Jianke Yang, Robin Walters, Yang, Jianke +5 · 8 citations
Computer Science · Materials Science · #Computational Physics and Python Applications #FOS: Computer and information sciences #Image Processing and 3D Reconstruction #Machine Learning (cs.LG) #Machine Learning in Materials Science
- Symmetries, flat minima, and the conserved quantities of gradient flow
2022/10/31 by Bo Zhao, Zhao, Bo, Iordan Ganev +7 · 7 citations
Computer Science · Physics and Astronomy · Engineering · #Adversarial Robustness in Machine Learning #Model Reduction and Neural Networks #Ion-surface interactions and analysis
- Physics-Guided Deep Learning for Dynamical Systems: A Survey
2021/07/02 by Rui Wang, Wang, Rui, Rose Yu +1 · 5 citations
Computer Science · Physics and Astronomy · #Computational Physics and Python Applications #FOS: Computer and information sciences #Machine Learning (cs.LG) #Model Reduction and Neural Networks #Neural Networks and Applications
- Can LLMs Understand Time Series Anomalies?
2024/10/07 by Zihao Zhou, Zhou, Zihao, Rose Yu +1 · 11 citations
Computer Science · Decision Sciences · Economics, Econometrics and Finance · #Complex Systems and Time Series Analysis #FOS: Computer and information sciences #Machine Learning (cs.LG) #Stock Market Forecasting Methods #Time Series Analysis and Forecasting
- Koopman Neural Forecaster for Time Series with Temporal Distribution Shifts
2022/10/07 by Rui Wang, Yihe Dong, Wang, Rui +5 · 5 citations
Computer Science · Physics and Astronomy · #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Model Reduction and Neural Networks #Time Series Analysis and Forecasting
- Neural Point Process for Learning Spatiotemporal Event Dynamics
2021/12/12 by Zihao Zhou, Xingyi Yang, Zhou, Zihao +7 · 4 citations
Mathematics · Engineering · #Point processes and geometric inequalities #3D Shape Modeling and Analysis
- ClimSim-Online: A Large Multi-scale Dataset and Framework for Hybrid ML-physics Climate Emulation
2023/06/14 by Sungduk Yu, Z W Hu, Yu, Sungduk +91 · 6 citations
Earth and Planetary Sciences · Physics and Astronomy · Environmental Science · #Meteorological Phenomena and Simulations #Model Reduction and Neural Networks #Hydrological Forecasting Using AI
- Understanding the Representation Power of Graph Neural Networks in Learning Graph Topology
2019/07/11 by Nima Dehmamy, Albert-Ĺaszló Barabási, Dehmamy, Nima +3 · 3 citations
Computer Science · Materials Science · Physics and Astronomy · #Advanced Graph Neural Networks #Complex Network Analysis Techniques #Data Analysis #FOS: Computer and information sciences #FOS: Physical sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Machine Learning in Materials Science #Statistics and Probability (physics.data-an)
- Finding Patient Zero: Learning Contagion Source with Graph Neural Networks
2020/06/21 by Chintan Shah, Shah, Chintan, Nima Dehmamy +11 · 3 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · Physics and Astronomy · #Advanced Graph Neural Networks #Bioinformatics and Genomic Networks #Complex Network Analysis Techniques #FOS: Computer and information sciences #Machine Learning (cs.LG) #Social and Information Networks (cs.SI)
- Multi-Modal Forecaster: Jointly Predicting Time Series and Textual Data
2024/11/11 by Kai Kim, Kim, Kai, Rajat Sen +11 · 9 citations
Computer Science · #Advanced Text Analysis Techniques
- Multi-Fidelity Residual Neural Processes for Scalable Surrogate Modeling
2024/02/29 by Ruijia Niu, Dongxia Wu, Niu, Ruijia +9 · 6 citations
Computer Science · Physics and Astronomy · Engineering · #Neural Networks and Applications #Model Reduction and Neural Networks #Advanced Data Processing Techniques
- Improving Convergence and Generalization Using Parameter Symmetries
2023/05/22 by Bo Zhao, Robert M. Gower, Zhao, Bo +5 · 4 citations
Computer Science · Physics and Astronomy · #Matrix Theory and Algorithms #Neural Networks and Applications #Scientific Research and Discoveries
- Symmetry Teleportation for Accelerated Optimization
2022/05/21 by Bo Zhao, Nima Dehmamy, Zhao, Bo +5 · 3 citations
Computer Science · #Machine Learning and ELM #Stochastic Gradient Optimization Techniques #Neural Networks and Applications
- Taming the Long Tail of Deep Probabilistic Forecasting
2022/02/27 by Jedrzej Kozerawski, Kozerawski, Jedrzej, Mayank Sharan +3 · 2 citations
Decision Sciences · Environmental Science · Computer Science · #Forecasting Techniques and Applications #Air Quality Monitoring and Forecasting #Gaussian Processes and Bayesian Inference
- Discovering Mixtures of Structural Causal Models from Time Series Data
2023/10/10 by Sumanth Varambally, Varambally, Sumanth, Yi-An Ma +3 · 2 citations
Computer Science · #Advanced Graph Neural Networks #Bayesian Modeling and Causal Inference #Explainable Artificial Intelligence (XAI) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Learning Granger Causality from Instance-wise Self-attentive Hawkes Processes
2024/02/06 by Dongxia Wu, Wu, Dongxia, Tsuyoshi Idé +13 · 2 citations
Mathematics · Biochemistry, Genetics and Molecular Biology · #Point processes and geometric inequalities #Diffusion and Search Dynamics
- Adapting While Learning: Grounding LLMs for Scientific Problems with Intelligent Tool Usage Adaptation
2024/11/01 by Bohan Lyu, Yadi Cao, Lyu, Bohan +11 · 2 voices · 2 citations
Computer Science · #Semantic Web and Ontologies #cs.AI #cs.CL #cs.LG
- Improving Learning to Optimize Using Parameter Symmetries
2025/04/21 by Guy Zamir, Aryan Dokania, Zamir, Guy +5 · 1 voice
Computer Science · Social Sciences · #FOS: Computer and information sciences #Machine Learning (cs.LG) #Mathematics Education and Teaching Techniques #Science Education and Pedagogy #Teaching and Learning Programming #cs.LG
- AtlasD: Automatic Local Symmetry Discovery
2025/04/15 by Manu Bhat, Jonghyun Park, Bhat, Manu +9 · 1 voice
Computer Science · #FOS: Computer and information sciences #Machine Learning (cs.LG) #cs.LG
- Disentangled Multi-Fidelity Deep Bayesian Active Learning
2023/05/07 by Dongxia Wu, Ruijia Niu, Wu, Dongxia +7 · 1 citation
Computer Science · Physics and Astronomy · #FOS: Computer and information sciences #Gaussian Processes and Bayesian Inference #Machine Learning (cs.LG) #Machine Learning and Algorithms #Model Reduction and Neural Networks
- Automatic Integration for Spatiotemporal Neural Point Processes
2023/10/09 by Zihao Zhou, Rose Yu, Zhou, Zihao +1 · 1 citation
Environmental Science · Medicine · #Air Quality and Health Impacts #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Optical Imaging and Spectroscopy Techniques
- Elucidated Rolling Diffusion Models for Probabilistic Forecasting of Complex Dynamics
2025/06/24 by Salva Rühling Cachay, Miika Aittala, Cachay, Salva Rühling +11 · 3 citations
Engineering · Environmental Science · #Artificial Intelligence (cs.AI) #Atmospheric and Oceanic Physics (physics.ao-ph) #Energy Load and Power Forecasting #FOS: Computer and information sciences #FOS: Physical sciences #Hydrological Forecasting Using AI #Hydrology and Drought Analysis #Machine Learning (cs.LG) #Machine Learning (stat.ML)
- Discovering Symbolic Differential Equations with Symmetry Invariants
2025/05/17 by Jianke Yang, Yang, Jianke, B. L. Hu +10 · 1 citation
Computer Science · Materials Science · Physics and Astronomy · #Evolutionary Algorithms and Applications #Machine Learning in Materials Science #Model Reduction and Neural Networks
- Breaking the Factorization Barrier in Diffusion Language Models
2026/02/09 by Ian Li, Zilei Shao, Benjie Wang +3 · 1 voice · 1 citation
#cs.LG #cs.AI