Workshop
Time Series in the Age of Large Models
Arjun Ashok · Imry Kissos · Kashif Rasul · Abdul Fatir Ansari · Moshe Unger · Pedro Mercado · Laurent Callot · Stephan Johannes
West Meeting Room 220-222
Sun 15 Dec, 8:15 a.m. PST
This workshop will delve into aspects of time series prediction and analysis in the age of large models, focusing on the topics of building foundation models for time series, leveraging pretrained models of other modalities for time series, multimodal time series models and time series evaluation and real-world applications.
Chat is not available.
Timezone: America/Los_Angeles
Schedule
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Sun 8:15 a.m. - 8:25 a.m.
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Opening Remarks
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Intro
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SlidesLive Video |
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Sun 8:25 a.m. - 9:00 a.m.
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Invited Talk by Tomas Pfister - Multimodal time series modeling
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Invited Talk
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SlidesLive Video |
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Sun 9:00 a.m. - 9:12 a.m.
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Partial Channel Dependence with Channel Masks for Time Series Foundation Model
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Oral
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link
SlidesLive Video |
Seunghan Lee · Taeyoung Park · Kibok Lee 🔗 |
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Sun 9:12 a.m. - 9:17 a.m.
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Time Series under Temporal Label Noise
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Spotlight
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link
SlidesLive Video |
Sujay Nagaraj · Walter Gerych · Sana Tonekaboni · Anna Goldenberg · Berk Ustun · Tom Hartvigsen 🔗 |
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Sun 9:17 a.m. - 9:29 a.m.
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PaPaGei: Open Foundation Models for Optical Physiological Signals
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Oral
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link
SlidesLive Video |
Arvind Pillai · Dimitrios Spathis · Fahim Kawsar · Mohammad Malekzadeh 🔗 |
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Sun 9:29 a.m. - 9:34 a.m.
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TimeSeriesExam: A Time Series Understanding Exam
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Spotlight
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link
SlidesLive Video |
Yifu Cai · Arjun Choudhry · Mononito Goswami · Artur Dubrawski 🔗 |
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Sun 9:34 a.m. - 10:35 a.m.
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Poster Session 1
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Poster Session
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Sun 10:35 a.m. - 11:10 a.m.
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Invited Talk by Christoph Bergmeir - Fundamental limitations of foundational forecasting models: The need for multimodality and rigorous evaluation
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Invited Talk
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SlidesLive Video |
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Sun 11:10 a.m. - 11:15 a.m.
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TimePFN: Effective Multivariate Time Series Forecasting with Synthetic Data
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Spotlight
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link
SlidesLive Video |
Ege Onur Taga · Muhammed Emrullah Ildiz · Samet Oymak 🔗 |
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Sun 11:15 a.m. - 11:50 a.m.
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Invited Talk by Valentina Zantedeschi - Forecasting for Decision Making: What Are We Missing?
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Invited Talk
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SlidesLive Video |
Valentina Zantedeschi 🔗 |
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Sun 12:00 p.m. - 1:00 p.m.
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Lunch Break
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Sun 1:00 p.m. - 2:00 p.m.
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Poster Session 2
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Poster Session
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Sun 2:00 p.m. - 2:35 p.m.
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Invited Talk by Qingsong Wen - LLM and Foundation Models for Time Series Analysis
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Invited Talk
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SlidesLive Video |
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Sun 2:35 p.m. - 2:47 p.m.
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Towards Time-Series Reasoning with LLMs
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Oral
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link
SlidesLive Video |
Winnie Chow · Lauren Gardiner · Haraldur Hallgrimsson · Maxwell Xu · Shirley Ren 🔗 |
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Sun 2:47 p.m. - 2:53 p.m.
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Benchmarking out-of-the-box forecasters of varying scales in biology
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Spotlight
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>
link
SlidesLive Video |
Anthony Culos · Mohammed AlQuraishi 🔗 |
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Sun 2:53 p.m. - 3:30 p.m.
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Coffee Break
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Sun 3:30 p.m. - 3:42 p.m.
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Scaling-laws for Large Time-series Models
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Oral
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link
SlidesLive Video |
JUSTIN ALSING · Thomas Edwards · Benjamin Wandelt · James Alvey · Nam Nguyen 🔗 |
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Sun 3:42 p.m. - 3:47 p.m.
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Towards Resolution-Aware Retrieval Augmented Zero-Shot Forecasting
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Spotlight
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link
SlidesLive Video |
Iman Deznabi · Peeyush Kumar · Madalina Fiterau 🔗 |
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Sun 3:47 p.m. - 4:22 p.m.
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Invited Talk by Mihaela van der Schaar - From Data to Discovery: LLM’s Role in Advancing Science
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Invited Talk
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SlidesLive Video |
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Sun 4:22 p.m. - 4:34 p.m.
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Maven: A Multimodal Foundation Model for Supernova Science
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Oral
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link
SlidesLive Video |
Gemma Zhang · Thomas Helfer · Alex Gagliano · Siddharth Mishra-Sharma · V Villar 🔗 |
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Sun 4:34 p.m. - 4:39 p.m.
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Mamba4Cast: Efficient Zero-Shot Time Series Forecasting with State Space Models
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Spotlight
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link
SlidesLive Video |
Sathya Kamesh Bhethanabhotla · Omar Swelam · Julien Siems · David Salinas · Frank Hutter 🔗 |
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Sun 4:39 p.m. - 5:14 p.m.
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Invited Talk by Andrew Gordon Wilson - Why Should We Develop Language Models for Time Series Forecasting?
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Invited Talk
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SlidesLive Video |
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Sun 5:14 p.m. - 5:19 p.m.
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Closing Remarks
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Outro
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SlidesLive Video |
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Masking the Gaps: An Imputation-Free Approach to Time Series Modeling with Missing Data ( Poster ) > link | Abhilash Neog · Arka Daw · Sepideh Fatemi Khorasgani · Anuj Karpatne 🔗 |
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MEDS-torch: An ML Pipleine for Inductive Experiments for EHR Medical Foundation Models ( Poster ) > link | Nassim Oufattole · Teya Bergamaschi · Pawel Renc · Aleksia Kolo · Matthew McDermott · Collin Stultz 🔗 |
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Generalized Prompt Tuning: How to Use a Frozen Pre-Trained Univariate Time Series Foundation Model for Multivariate Time Series Prediction ( Poster ) > link | Mingzhu Liu · Angela Chen · George H Chen 🔗 |
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Efficient Time Series Processing for Transformers and State-Space Models through Token Merging ( Poster ) > link | Leon Götz · Marcel Kollovieh · Stephan Günnemann · Leo Schwinn 🔗 |
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Towards Large-scale Clinical Multi-variate Time-series Datasets ( Poster ) > link |
13 presentersManuel Burger · Fedor Sergeev · Malte Londschien · Daphné Chopard · Hugo Yèche · Eike Gerdes · Polina Leshetkina · Alexander Morgenroth · Zeynep Babür · Jasmina Bogojeska · Martin Faltys · Rita Kuznetsova · Gunnar Rätsch |
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Scaling to Billion Parameters for Time Series Foundation Models with Mixture of Experts ( Poster ) > link | Xiaoming Shi · Shiyu Wang · Yuqi Nie · Dianqi Li · Zhou Ye · Qingsong Wen · Ming Jin 🔗 |
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Optimizing Time Series Forecasting Architectures: A Hierarchical Neural Architecture Search Approach
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Poster
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link
SlidesLive Video |
Difan Deng · Marius Lindauer 🔗 |
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LETS-C: Leveraging Text Embedding for Time Series Classification
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Poster
)
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link
SlidesLive Video |
Rachneet Kaur · Zhen Zeng · Tucker Balch · Manuela Veloso 🔗 |
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Unveiling and Manipulating Concepts in Time Series Foundation Models ( Poster ) > link | Michal Wilinski · Mononito Goswami · Nina Żukowska · Willa Potosnak · Artur Dubrawski 🔗 |
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From RNNs to Foundation Models: An Empirical Study on Commercial Building Energy Consumption ( Poster ) > link | Shourya Bose · Yijiang Li · Amy Van Sant · Yu Zhang · Kibaek Kim 🔗 |
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♠ SPADE ♠ Split Peak Attention DEcomposition ( Poster ) > link |
11 presentersMalcolm Wolff · Kin Gutierrez · Boris Oreshkin · Sunny Ruan · Sitan Yang · Abhinav Katoch · Shankar Ramasubramanian · Youxin Zhang · Michael Mahoney · Dmitry Efimov · Vincent Quenneville-Belair |
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TrajGPT: Healthcare Time-Series Representation Learning for Trajectory Prediction
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Poster
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link
SlidesLive Video |
Ziyang Song · Qincheng Lu · Mike He Zhu · David Buckeridge · Yue Li 🔗 |
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Test-Time Learning For Time Series Forecasting ( Poster ) > link | Panayiotis Christou · Shichu Chen · Xupeng Chen · Parijat Dube 🔗 |
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Unveiling the Potential of Text in High-Dimensional Time Series Forecasting ( Poster ) > link | Xin Zhou · Weiqing Wang · SHILIN QU · Zhiqiang Zhang · Christoph Bergmeir 🔗 |
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LiMTR: Time Series Motion Prediction for Diverse Road Users through Multimodal Feature Integration ( Poster ) > link | Camiel Oerlemans · Bram Grooten · Michiel Braat · Alaa Alassi · Emilia Silvas · Decebal Constantin Mocanu 🔗 |
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Measuring Pre-training Data Quality without Labels for Time Series Foundation Models ( Poster ) > link | Songkang Wen · Vasilii Feofanov · Jianfeng Zhang 🔗 |
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Domain-adapted Lag-Llama for Time Series Forecasting in the African Retail Sector. ( Poster ) > link | Kelian Massa · Dario Fanucchi 🔗 |
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Effectively Leveraging Exogenous Information across Neural Forecasters ( Poster ) > link | Andres Potapczynski · Kin Gutierrez · Malcolm Wolff · Andrew Wilson · Dmitry Efimov · Vincent Quenneville-Belair 🔗 |
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Transformer-based Time-Series Biomarker Discovery for COPD Diagnosis ( Poster ) > link | Soham Gadgil · Joshua Galanter · Mohammadreza Negahdar 🔗 |
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The Tabular Foundation Model TabPFN Outperforms Specialized Time Series Forecasting Models Based on Simple Features ( Poster ) > link | Shi Bin Hoo · Samuel Müller · David Salinas · Frank Hutter 🔗 |
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Probabilistic Forecasting for Building Energy Systems: Are Time-Series Foundation Models the Answer? ( Poster ) > link | Young-Jin Park · François Germain · Jing Liu · Ye Wang · Gordon Wichern · Toshiaki Koike-Akino · Navid Azizan · Christopher Laughman · Ankush Chakrabarty 🔗 |
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Fine-Tuning a Time Series Foundation Model with Wasserstein Loss
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Poster
)
>
link
SlidesLive Video |
Andrei Chernov 🔗 |
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Reimagining Time Series Foundation Models: Metadata and State-Space Model Perspectives
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Poster
)
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link
SlidesLive Video |
Pengrui Quan · Ozan Mulayim · Liying Han · Dezhi Hong · Mario Berges · Mani Srivastava 🔗 |
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When Larger Isn’t Better: Lightweight CNNs Outperform Large Time-Series Models in Classification of Oil and Gas Drilling Data ( Poster ) > link | abdallah benzine · J.S. Buiting · Soumyadipta Sengupta · Badal Gupta · Youssef Tamaazousti 🔗 |
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Do we really need Foundation Models for multi-step-ahead Epidemic Forecasting? ( Poster ) > link | Mrinmoy Dey · Aprameyo Chakrabartty · Dhruv Sarkar · Tanujit Chakraborty 🔗 |
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A Language Model-Guided Framework for Mining Time Series with Distributional Shifts
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Poster
)
>
link
SlidesLive Video |
Haibei Zhu · Yousef El-Laham · Elizabeth Fons · Svitlana Vyetrenko 🔗 |
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GIFT-Eval: A Benchmark for General Time Series Forecasting Model Evaluation ( Poster ) > link | Ibrahim Taha Aksu · Gerald Woo · Juncheng Liu · Xu Liu · Chenghao Liu · Silvio Savarese · Caiming Xiong · Doyen Sahoo 🔗 |
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Enhancing Multivariate Time Series Forecasting via Multi-Task Learning and Random Matrix Theory
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Poster
)
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link
SlidesLive Video |
Romain Ilbert · Malik Tiomoko · Cosme Louart · Vasilii Feofanov · Themis Palpanas · Ievgen Redko 🔗 |
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Beyond LoRA: Exploring Efficient Fine-Tuning Techniques for Time Series Foundational Models ( Poster ) > link | Divij Gupta · Anubhav Bhatti · Surajsinh Parmar 🔗 |
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Incorporating Metabolic Information into LLMs for Anomaly Detection in Clinical Time-Series ( Poster ) > link | Maxx Richard Rahman · Ruoxuan Liu · Wolfgang Maass 🔗 |
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Zero shot time series forecasting using Kolgomorov Arnold Networks
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Poster
)
>
link
SlidesLive Video |
Abhiroop Bhattacharya · Nandinee Haq 🔗 |
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Critical Evaluation of Time Series Foundation Models in Demand Forecasting ( Poster ) > link | Santosh Puvvada · Satyajit Chaudhuri 🔗 |
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Context is Key: A Benchmark for Forecasting with Essential Textual Information ( Poster ) > link |
11 presentersArjun Ashok · Andrew Williams · Étienne Marcotte · Valentina Zantedeschi · Jithendaraa Subramanian · Roland Riachi · James Requeima · Alexandre Lacoste · Irina Rish · Nicolas Chapados · Alexandre Drouin |
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Revisiting Masked Auto-Encoders for ECG-Language Representation Learning ( Poster ) > link | HUNG MANH PHAM · Aaqib Saeed · Dong Ma 🔗 |
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Weakly-supervised Multi-sensor Anomaly Detection with Time-series Foundation Models ( Poster ) > link | Zelin He · Matthew Reimherr · Sarah Alnegheimish · Akash Chandrayan 🔗 |
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UniTST: Effectively Modeling Inter-Series and Intra-Series Dependencies for Multivariate Time Series Forecasting ( Poster ) > link | Juncheng Liu · Chenghao Liu · Gerald Woo · Yiwei Wang · Bryan Hooi · Caiming Xiong · Doyen Sahoo 🔗 |
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KAN4Drift: Are KAN Effective for Identifying and Tracking Concept Drift in Time Series? ( Poster ) > link | Kunpeng Xu · Lifei Chen · Shengrui Wang 🔗 |
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Text2Freq: Learning Series Patterns from Text via Frequency Domain ( Poster ) > link | Ming-Chih Lo · Ching Chang · Wen-Chih Peng 🔗 |
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In-context Quantile Regression for Multi-product Inventory Management using Time-series Transformers
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Poster
)
>
link
SlidesLive Video |
Magnus Josef Maichle · Sohom Mukherjee · Kai Michael Günder · Ivane Antonov · Nikolai Stein · Richard Pibernik 🔗 |
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Implicit Reasoning in Deep Time Series Forecasting ( Poster ) > link | Willa Potosnak · Cristian Challu · Mononito Goswami · Michal Wilinski · Nina Żukowska · Artur Dubrawski 🔗 |
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Preventing Conflicting Gradients in Neural Temporal Point Process Models for Irregular Time Series Data ( Poster ) > link | Tanguy Bosser · Souhaib Ben Taieb 🔗 |
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Enhance Time Series Modeling by Integrating LLM ( Poster ) > link | Can (Sam) Chen · Gabriel Oliveira · Hossein Sharifi-Noghabi · Tristan Sylvain 🔗 |
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General-Purpose Brain Foundation Models for Time-Series Neuroimaging Data ( Poster ) > link | Mohammad Javad Darvishi Bayazi · Hena Ghonia · Roland Riachi · Bruno Aristimunha · Arian Khorasani · Md Rifat Arefin · Amin Darabi · Guillaume Dumas · Irina Rish 🔗 |
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Towards Long-Context Time Series Foundation Models ( Poster ) > link | Nina Żukowska · Mononito Goswami · Michal Wilinski · Willa Potosnak · Artur Dubrawski 🔗 |
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Joint Embedding go Temporal ( Poster ) > link | Sofiane ENNADIR · Siavash Golkar · Leopoldo Sarra 🔗 |
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Towards Unbiased Evaluation of Time-series Anomaly Detector
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Poster
)
>
link
SlidesLive Video |
Debarpan Bhattacharya · Sumanta Mukherjee · Chandramouli Kamanchi · Vijay Ekambaram · Arindam Jati · Pankaj Dayama 🔗 |
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Leveraging Periodicity for Robustness with Multi-modal Mood Pattern Models ( Poster ) > link | Jaya Narain · Qinhua Sun · Oussama Elachqar · Haraldur Hallgrimsson · Feng Zhu · Shirley Ren 🔗 |
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Sequential Order-Robust Mamba for Time Series Forecasting ( Poster ) > link | Seunghan Lee · Juri Hong · Kibok Lee · Taeyoung Park 🔗 |
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Align and Fine-Tune: Enhancing LLMs for Time-Series Forecasting ( Poster ) > link | Ching Chang · Wei-Yao Wang · Wen-Chih Peng · Tien-Fu Chen · Sagar Samtani 🔗 |
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LLMForecaster: Improving Seasonal Event Forecasts with Unstructured Textual Data ( Poster ) > link | Hanyu Zhang · Chuck Arvin · Dmitry Efimov · Michael Mahoney · Dominique Perrault-Joncas · Shankar Ramasubramanian · Andrew Wilson · Malcolm Wolff 🔗 |
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Mixture of Experts for Time Series Foundation Models ( Poster ) > link | Xu Liu · Juncheng Liu · Gerald Woo · Ibrahim Taha Aksu · Chenghao Liu · Silvio Savarese · Caiming Xiong · Doyen Sahoo 🔗 |
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Deep Temporal Deaggregation: Large-Scale Spatio-Temporal Generative Models ( Poster ) > link | David Bergström · Mattias Tiger · Fredrik Heintz 🔗 |
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Hierarchical Time Series Forecasting Via Latent Mean Encoding ( Poster ) > link | Alessandro Salatiello · Stefan Birr · Manuel Kunz 🔗 |
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PRIMUS: Pretraining IMU Encoders with Multimodal and Self-Supervised Learning ( Poster ) > link | Arnav Das · Chi Ian Tang · Fahim Kawsar · Mohammad Malekzadeh 🔗 |
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Stochastic Sparse Sampling: A Framework for Local Explainability in Variable-Length Medical Time Series ( Poster ) > link | Xavier Mootoo · ALAN DIAZ-MONTIEL · Milad Lankarany · Hina Tabassum 🔗 |
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Adaptive Information Routing for Multi Modal Time Series Forecasting ( Poster ) > link | Jun Seo · Hyeokjun Choe · Seohui Bae · Soyeon Park · Jinseok Yang · Dongwan Kang · Woohyung Lim 🔗 |
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Catching the Spikes: Heteroscedastic Uncertainty Quantification for Enhanced Malaria Prediction ( Poster ) > link | Feng Chen · Qi Qi · Jiayu Qiu · Kemeng Zhang · Xiang Li 🔗 |
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Electrocardiogram Report Generation and Question Answering via Retrieval-Augmented Self-Supervised Modeling ( Poster ) > link | jialu tang · Tong Xia · Yuan Lu · Cecilia Mascolo · Aaqib Saeed 🔗 |