conftrace_

Liang Sun

34 papers · 2008–2026 · 10 conferences · across top CS/AI conferences

Achievements

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+15 more ↓ πŸ—ΊοΈ Taxonomy Completionist (14) 🧭 Keyword Pioneer πŸŒ‰ Interdisciplinary Bridge 🌈 Renaissance Researcher (5) 🐣 Hot Topic Early Bird
πŸŒ‰ Interdisciplinary Bridge πŸƒ Academic Marathon (17) πŸ—ΊοΈ Taxonomy Completionist (14) 🌟 Keyword Trendsetter Combo (6) 🀝 Dynamic Duo (14) πŸ‘‘ Triple Crown πŸ† Grand Slam 🌱 Topic Pioneer πŸ† Keyword Champion (2) πŸ”₯ Unstoppable (5) πŸš€ Conference Pioneer πŸ—ƒοΈ Keyword Collector (144) ⚑ Prolific Year (6) πŸ’Ž Century Club (33) πŸ“ˆ Trend Setter

Conferences

NIPS (10) IJCAI (7) AAAI (6) ICML (4) ICLR (2) ACL (1) CVPR (1) EMNLP (1) ICCV (1) IJCNLP (1)

Papers

MoCast: Learning Turbulent Motions Under Physical Guidance for Precipitation Nowcasting AAAI 2026 SCNNs: Spike-based Coupling Neural Networks for Understanding Structural-Functional Relationships in the Human Brain IJCAI 2025 Learning to Extrapolate and Adjust: Two-Stage Meta-Learning for Concept Drift in Online Time Series Forecasting IJCAI 2025 Integrating Neurosymbolic AI in Advanced Air Mobility: A Comprehensive Survey IJCAI 2025 A Non-isotropic Time Series Diffusion Model with Moving Average Transitions ICML 2025 DeeperForward: Enhanced Forward-Forward Training for Deeper and Better Performance ICLR 2025 WeatherGNN: Exploiting Meteo- and Spatial-Dependencies for Local Numerical Weather Prediction Bias-Correction IJCAI 2024 Task-oriented Time Series Imputation Evaluation via Generalized Representers NIPS 2024 APSeg: Auto-Prompt Network for Cross-Domain Few-Shot Semantic Segmentation CVPR 2024 RobustTSF: Towards Theory and Design of Robust Time Series Forecasting with Anomalies ICLR 2024 BayOTIDE: Bayesian Online Multivariate Time Series Imputation with Functional Decomposition ICML 2024 Explain Temporal Black-Box Models via Functional Decomposition ICML 2024 AHPA: Adaptive Horizontal Pod Autoscaling Systems on Alibaba Cloud Container Service for Kubernetes AAAI 2023 Transformers in Time Series: A Survey IJCAI 2023 eForecaster: Unifying Electricity Forecasting with Robust, Flexible, and Explainable Machine Learning Algorithms AAAI 2023 OneNet: Enhancing Time Series Forecasting Models under Concept Drift by Online Ensembling NIPS 2023 One Fits All: Power General Time Series Analysis by Pretrained LM NIPS 2023 A Hybrid Causal Structure Learning Algorithm for Mixed-Type Data AAAI 2022 Towards Out-of-Distribution Sequential Event Prediction: A Causal Treatment NIPS 2022 FiLM: Frequency improved Legendre Memory Model for Long-term Time Series Forecasting NIPS 2022 FEDformer: Frequency Enhanced Decomposed Transformer for Long-term Series Forecasting ICML 2022 Time Series Data Augmentation for Deep Learning: A Survey IJCAI 2021 Learning Interpretable Decision Rule Sets: A Submodular Optimization Approach NIPS 2021 RobustTrend: A Huber Loss with a Combined First and Second Order Difference Regularization for Time Series Trend Filtering IJCAI 2019 RobustSTL: A Robust Seasonal-Trend Decomposition Algorithm for Long Time Series AAAI 2019 Exploring Overall Contextual Information for Image Captioning in Human-Like Cognitive Style ICCV 2019 Which Factorization Machine Modeling Is Better: A Theoretical Answer with Optimal Guarantee AAAI 2019 Parse Imputation for Dependency Annotations IJCNLP 2015 Parse Imputation for Dependency Annotations ACL 2015 Parsing low-resource languages using Gibbs sampling for PCFGs with latent annotations EMNLP 2014 Projection onto A Nonnegative Max-Heap NIPS 2011 Efficient Recovery of Jointly Sparse Vectors NIPS 2009 Learning Brain Connectivity of Alzheimer's Disease from Neuroimaging Data NIPS 2009 Multi-label Multiple Kernel Learning NIPS 2008