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ICLR (2023-2024)

---2024---

  1. A Generative Pre-Training Framework for Spatio-Temporal Graph Transfer Learning. https://openreview.net/forum?id=QyFm3D3Tzi

  2. AirPhyNet: Harnessing Physics-Guided Neural Networks for Air Quality Prediction. https://openreview.net/forum?id=JW3jTjaaAB

  3. Biased Temporal Convolution Graph Network for Time Series Forecasting with Missing Values. https://openreview.net/forum?id=O9nZCwdGcG

  4. Beyond Spatio-Temporal Representations: Evolving Fourier Transform for Temporal Graphs. https://openreview.net/forum?id=uvFhCUPjtI

  5. Bayesian Optimization through Gaussian Cox Process Models for Spatio-temporal Data. https://openreview.net/forum?id=9j1RD9LlWH

  6. ClimODE: Climate Forecasting With Physics-informed Neural ODEs. https://openreview.net/forum?id=xuY33XhEGR

  7. Conditional Information Bottleneck Approach for Time Series Imputation. https://openreview.net/forum?id=K1mcPiDdOJ

  8. CARD: Channel Aligned Robust Blend Transformer for Time Series Forecasting. https://openreview.net/forum?id=MJksrOhurE

  9. Copula Conformal prediction for multi-step time series prediction. https://openreview.net/forum?id=ojIJZDNIBj

  10. CausalTime: Realistically Generated Time-series for Benchmarking of Causal Discovery. https://openreview.net/forum?id=iad1yyyGme

  11. Causality-Inspired Spatial-Temporal Explanations for Dynamic Graph Neural Networks. https://openreview.net/forum?id=AJBkfwXh3u

  12. Diffusion-TS: Interpretable Diffusion for General Time Series Generation. https://openreview.net/forum?id=4h1apFjO99

  13. Disentangling Time Series Representations via Contrastive based $l$− Variational Inference. https://openreview.net/forum?id=iI7hZSczxE

  14. DAM: A Foundation Model for Forecasting. https://openreview.net/forum?id=4NhMhElWqP

  15. FITS: Modeling Time Series with 10$k$ Parameters. https://openreview.net/forum?id=bWcnvZ3qMb

  16. Explaining Time Series via Contrastive and Locally Sparse Perturbations. https://openreview.net/forum?id=qDdSRaOiyb

  17. Generative Learning for Financial Time Series with Irregular and Scale-Invariant Patterns. https://openreview.net/forum?id=CdjnzWsQax

  18. GAFormer: Enhancing Timeseries Transformers Through Group-Aware Embeddings. https://openreview.net/forum?id=c56TWtYp0W

  19. Generative Modeling of Regular and Irregular Time Series Data via Koopman VAEs. https://openreview.net/forum?id=eY7sLb0dVF

  20. GeoLLM: Extracting Geospatial Knowledge from Large Language Models. https://openreview.net/forum?id=TqL2xBwXP3

  21. Inherently Interpretable Time Series Classification via Multiple Instance Learning. https://openreview.net/forum?id=xriGRsoAza

  22. iTransformer: Inverted Transformers Are Effective for Time Series Forecasting. https://openreview.net/forum?id=JePfAI8fah

  23. Interpretable Sparse System Identification: Beyond Recent Deep Learning Techniques on Time-Series Prediction. https://openreview.net/forum?id=aFWUY3E7ws

  24. Interpretable Sparse System Identification: Beyond Recent Deep Learning Techniques on Time-Series Prediction. https://openreview.net/forum?id=aFWUY3E7ws

  25. Leveraging Generative Models for Unsupervised Alignment of Neural Time Series Data. https://openreview.net/forum?id=9zhHVyLY4K

  26. Learning to Embed Time Series Patches Independently. https://openreview.net/forum?id=WS7GuBDFa2

  27. ModernTCN: A Modern Pure Convolution Structure for General Time Series Analysis. https://openreview.net/forum?id=vpJMJerXHU

  28. Multi-Resolution Diffusion Models for Time Series Forecasting. https://openreview.net/forum?id=mmjnr0G8ZY

  29. MG-TSD: Multi-Granularity Time Series Diffusion Models with Guided Learning Process. https://openreview.net/forum?id=CZiY6OLktd

  30. Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting. https://openreview.net/forum?id=lJkOCMP2aW

  31. NuwaDynamics: Discovering and Updating in Causal Spatio-Temporal Modeling. https://openreview.net/forum?id=sLdVl0q68X

  32. Parametric Augmentation for Time Series Contrastive Learning. https://openreview.net/forum?id=EIPLdFy3vp

  33. Periodicity Decoupling Framework for Long-term Series Forecasting. https://openreview.net/forum?id=dp27P5HBBt

  34. Retrieval-Based Reconstruction For Time-series Contrastive Learning. https://openreview.net/forum?id=3zQo5oUvia

  35. Rethinking Channel Dependence for Multivariate Time Series Forecasting: Learning from Leading Indicators. https://openreview.net/forum?id=JiTVtCUOpS

  36. RobustTSF: Towards Theory and Design of Robust Time Series Forecasting with Anomalies. https://openreview.net/forum?id=ltZ9ianMth

  37. SocioDojo: Building Lifelong Analytical Agents with Real-world Text and Time Series. https://openreview.net/forum?id=s9z0HzWJJp

  38. Soft Contrastive Learning for Time Series. https://openreview.net/forum?id=pAsQSWlDUf

  39. Stable Neural Stochastic Differential Equations in Analyzing Irregular Time Series Data. https://openreview.net/forum?id=4VIgNuQ1pY

  40. STanHop: Sparse Tandem Hopfield Model for Memory-Enhanced Time Series Prediction. https://openreview.net/forum?id=6iwg437CZs

  41. Self-Supervised Contrastive Forecasting. https://openreview.net/forum?id=nBCuRzjqK7

  42. Transformer-Modulated Diffusion Models for Probabilistic Multivariate Time Series Forecasting. https://openreview.net/forum?id=qae04YACHs

  43. Time-LLM: Time Series Forecasting by Reprogramming Large Language Models. https://openreview.net/forum?id=Unb5CVPtae

  44. TEST: Text Prototype Aligned Embedding to Activate LLM's Ability for Time Series. https://openreview.net/forum?id=Tuh4nZVb0g

  45. TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting. https://openreview.net/forum?id=YH5w12OUuU

  46. Towards Enhancing Time Series Contrastive Learning: A Dynamic Bad Pair Mining Approach. https://openreview.net/forum?id=K2c04ulKXn

  47. TACTiS-2: Better, Faster, Simpler Attentional Copulas for Multivariate Time Series. https://openreview.net/forum?id=xtOydkE1Ku

  48. Towards Transparent Time Series Forecasting. https://openreview.net/forum?id=TYXtXLYHpR

  49. TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting. https://openreview.net/forum?id=7oLshfEIC2

  50. T-Rep: Representation Learning for Time Series using Time-Embeddings. https://openreview.net/forum?id=3y2TfP966N

  51. TESTAM: A Time-Enhanced Spatio-Temporal Attention Model with Mixture of Experts. https://openreview.net/forum?id=N0nTk5BSvO

  52. VQ-TR: Vector Quantized Attention for Time Series Forecasting. https://openreview.net/forum?id=IxpTsFS7mh

---2023---

  1. A Time Series is Worth 64 Words: Long-term Forecasting with Transformers. Yuqi Nie, Nam H Nguyen, Phanwadee Sinthong, Jayant Kalagnanam. paper #time-series-forecasting

  2. BSTT: A Bayesian Spatial-Temporal Transformer for Sleep Staging. Yuchen Liu, Ziyu Jia. paper #sleep-staging

  3. Crossformer: Transformer Utilizing Cross-Dimension Dependency for Multivariate Time Series Forecasting. Yunhao Zhang, Junchi Yan. paper #time-series-forecasting

  4. Contrastive Learning for Unsupervised Domain Adaptation of Time Series. Yilmazcan Ozyurt, Stefan Feuerriegel, Ce Zhang. paper #unsupervised-domain-adaptation #time-series

  5. CUTS: Neural Causal Discovery from Irregular Time-Series Data. Yuxiao Cheng, Runzhao Yang, Tingxiong Xiao, Zongren Li, Jinli Suo, Kunlun He, Qionghai Dai. paper #causal-discover #irregular-time-series

  6. Learning Fast and Slow for Online Time Series Forecasting. Quang Pham, Chenghao Liu, Doyen Sahoo, Steven Hoi. paper #online-time-series-forecasting

  7. Leveraging Future Relationship Reasoning for Vehicle Trajectory Prediction. Daehee Park, Hobin Ryu, Yunseo Yang, Jegyeong Cho, Jiwon Kim, Kuk-Jin Yoon. paper #vehicle-trajectory-prediction

  8. MICN: Multi-scale Local and Global Context Modeling for Long-term Series Forecasting. Huiqiang Wang, Jian Peng, Feihu Huang, Jince Wang, Junhui Chen, Yifei Xiao. Yuqi Nie, Nam H Nguyen, Phanwadee Sinthong, Jayant Kalagnanam. paper #long-term-series-forecasting

  9. Scaleformer: Iterative Multi-scale Refining Transformers for Time Series Forecasting. Mohammad Amin Shabani, Amir H. Abdi, Lili Meng, Tristan Sylvain. paper #time-series-forecasting

  10. Sequential Latent Variable Models for Few-Shot High-Dimensional Time-Series Forecasting. Xiajun Jiang, Ryan Missel, Zhiyuan Li, Linwei Wang. paper #time-series-forecasting

  11. Temporal Dependencies in Feature Importance for Time Series Prediction. Kin Kwan Leung, Clayton Rooke, Jonathan Smith, Saba Zuberi, Maksims Volkovs. paper #time-series-prediction

  12. TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis. Haixu Wu, Tengge Hu, Yong Liu, Hang Zhou, Jianmin Wang, Mingsheng Long. paper #time-series-analysis

  13. Out-of-distribution Representation Learning for Time Series Classification. Wang Lu, Jindong Wang, Xinwei Sun, Yiqiang Chen, Xing Xie. paper #time-series-classification

  14. Unsupervised Model Selection for Time Series Anomaly Detection. Mononito Goswami, Cristian Ignacio Challu, Laurent Callot, Lenon Minorics, Andrey Kan. paper #time-series-anomaly-detection