ForecastPFN: Synthetically-Trained Zero-Shot Forecasting

Neural Information Processing Systems (NeurIPS), 2023

3 November 2023

Samuel Dooley

Gurnoor Singh Khurana

Papers citing "ForecastPFN: Synthetically-Trained Zero-Shot Forecasting"

33 / 33 papers shown

Title
TempoPFN: Synthetic Pre-training of Linear RNNs for Zero-shot Time Series Forecasting Vladyslav Moroshan Julien N. Siems Arber Zela Timur Carstensen Frank Hutter AI4TS AI4CE 159 0 0 29 Oct 2025
Foundation Model Forecasts: Form and Function Alvaro Perez-Diaz James C. Loach Danielle E. Toutoungi Lee Middleton AI4TS 96 0 0 22 Oct 2025
Time Series Foundation Models: Benchmarking Challenges and Requirements Marcel Meyer Sascha Kaltenpoth Kevin Zalipski Oliver Müller AI4TS 128 1 0 15 Oct 2025
Towards Foundation Models for Zero-Shot Time Series Anomaly Detection: Leveraging Synthetic Data and Relative Context Discrepancy Tian-Shing Lan Hao Duong Le Jinbo Li Wenjun He Meng Wang Chenghao Liu Chen Zhang AI4TS 231 1 0 25 Sep 2025
One-Embedding-Fits-All: Efficient Zero-Shot Time Series Forecasting by a Model Zoo Hao-Nan Shi Ting Huang Lu Han De-Chuan Zhan Han-Jia Ye AI4TS 142 0 0 04 Sep 2025
FoMEMO: Towards Foundation Models for Expensive Multi-objective Optimization Yiming Yao Fei Liu Liang Zhao Xi Lin Qingfu Zhang 76 0 0 03 Sep 2025
Amortized In-Context Mixed Effect Transformer Models: A Zero-Shot Approach for Pharmacokinetics César Ali Ojeda Marin W. Huisinga Purity Kavwele Niklas Hartung 72 1 0 21 Aug 2025
DP-GPT4MTS: Dual-Prompt Large Language Model for Textual-Numerical Time Series Forecasting Chanjuan Liu Shengzhi Wang Enqiang Zhu AI4TS 47 1 0 06 Aug 2025
Diffusion Models for Time Series Forecasting: A Survey Chen Su Zhengzhou Cai Yuanhe Tian Zhuochao Chang Zihong Zheng Yan Song AI4TS 132 1 0 19 Jul 2025
Time Series Forecasting as Reasoning: A Slow-Thinking Approach with Reinforced LLMs Yucong Luo Yitong Zhou Mingyue Cheng Jiahao Wang Daoyu Wang Tingyue Pan Jintao Zhang AI4TS LRM 224 6 0 12 Jun 2025
Do-PFN: In-Context Learning for Causal Effect Estimation Jake Robertson Arik Reuter Siyuan Guo Noah Hollmann Katharina Eggensperger Bernhard Schölkopf CML 358 7 0 06 Jun 2025
Position: The Future of Bayesian Prediction Is Prior-Fitted Samuel G. Müller Arik Reuter Noah Hollmann David Rügamer Katharina Eggensperger 146 4 0 29 May 2025
Bayesian Neural Scaling Law Extrapolation with Prior-Data Fitted Networks Dongwoo Lee Dong Bok Lee Steven Adriaensen Juho Lee Sung Ju Hwang Frank Hutter Seon Joo Kim Hae Beom Lee BDL 296 0 0 29 May 2025
BLAST: Balanced Sampling Time Series Corpus for Universal Forecasting Models Zezhi Shao Yujie Li Fei Wang Chengqing Yu Yisong Fu Tangwen Qian Bin Xu Boyu Diao Yongjun Xu Xueqi Cheng AI4TS 205 10 0 23 May 2025
Context parroting: A simple but tough-to-beat baseline for foundation models in scientific machine learning Yuanzhao Zhang William Gilpin AI4TS 171 1 0 16 May 2025
SeqFusion: Sequential Fusion of Pre-Trained Models for Zero-Shot Time-Series Forecasting Ting Huang Xu-Yang Chen Han-Jia Ye AI4TS 179 2 0 04 Mar 2025
In-context learning of evolving data streams with tabular foundational models Afonso Lourenço João Gama Eric P. Xing Goreti Marreiros 275 0 0 24 Feb 2025
TimePFN: Effective Multivariate Time Series Forecasting with Synthetic DataAAAI Conference on Artificial Intelligence (AAAI), 2025 Ege Onur Taga M. E. Ildiz Samet Oymak AI4TS 254 12 0 22 Feb 2025
EquiTabPFN: A Target-Permutation Equivariant Prior Fitted Networks Michael Arbel David Salinas Katharina Eggensperger 356 4 0 10 Feb 2025
FlexTSF: A Flexible Forecasting Model for Time Series with Variable Regularities Jingge Xiao Yile Chen Gao Cong Wolfgang Nejdl Simon Gottschalk AI4TS 248 0 0 30 Oct 2024
Strada-LLM: Graph LLM for traffic prediction Seyed Mohamad Moghadas Yangxintong Lyu Alexandre Alahi Alexandre Alahi AI4TS 419 4 0 28 Oct 2024
ForecastBench: A Dynamic Benchmark of AI Forecasting CapabilitiesInternational Conference on Learning Representations (ICLR), 2024 Ezra Karger Houtan Bastani Chen Yueh-Han Zachary Jacobs Danny Halawi Fred Zhang P. Tetlock 426 24 0 30 Sep 2024
Zero-shot forecasting of chaotic systemsInternational Conference on Learning Representations (ICLR), 2024 Yuanzhao Zhang William Gilpin AI4TS 531 15 0 24 Sep 2024
ViTime: Foundation Model for Time Series Forecasting Powered by Vision Intelligence Luoxiao Yang Yun Wang Xinqi Fan Israel Cohen Jingdong Chen Yue Zhao AI4TS 292 11 0 10 Jul 2024
Towards a General Time Series Anomaly Detector with Adaptive Bottlenecks and Dual Adversarial Decoders Qichao Shentu Beibu Li Kai Zhao Yang Shu Zhongwen Rao Lujia Pan Bin Yang Chenjuan Guo AI4TS 365 17 0 24 May 2024
Large language models can be zero-shot anomaly detectors for time series? Sarah Alnegheimish Linh Nguyen Laure Berti-Equille K. Veeramachaneni AI4TS 231 29 0 23 May 2024
Towards Foundation Time Series Model: To Synthesize Or Not To Synthesize? Kseniia Kuvshinova Olga Tsymboi Alina Kostromina Dmitry Simakov Elizaveta Kovtun AI4TS 170 3 0 04 Mar 2024
Generative Pretrained Hierarchical Transformer for Time Series Forecasting Zhiding Liu Jiqian Yang Mingyue Cheng Yucong Luo Zhi Li AI4TS 155 36 0 26 Feb 2024
Only the Curve Shape Matters: Training Foundation Models for Zero-Shot Multivariate Time Series Forecasting through Next Curve Shape Prediction Cheng Feng Long Huang Denis Krompass AI4TS 288 9 0 12 Feb 2024
Is Mamba Capable of In-Context Learning? Riccardo Grazzi Julien N. Siems Simon Schrodi Thomas Brox Frank Hutter 183 54 0 05 Feb 2024
LLMs learn governing principles of dynamical systems, revealing an in-context neural scaling law Toni J. B. Liu Nicolas Boullé Raphaël Sarfati Christopher Earls AI4TS 187 29 0 01 Feb 2024
Towards Urban General Intelligence: A Review and Outlook of Urban Foundation Models Weijiao Zhang Jindong Han Zhao Xu Hang Ni Hao Liu Hui Xiong Hui Xiong AI4CE 458 24 0 30 Jan 2024
Efficient Bayesian Learning Curve Extrapolation using Prior-Data Fitted NetworksNeural Information Processing Systems (NeurIPS), 2023 Steven Adriaensen Herilalaina Rakotoarison Samuel G. Müller Katharina Eggensperger BDL 214 37 0 31 Oct 2023