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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
Project Page [ OpenReview] 

Abstract

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Schedule

Timezone: America/Los_Angeles
8:15 AM
Opening Remarks
9:00 AM
Partial Channel Dependence with Channel Masks for Time Series Foundation Model
Seunghan Lee ⋅ Taeyoung Park ⋅ Kibok Lee
9:12 AM
Time Series under Temporal Label Noise
Sujay Nagaraj ⋅ Walter Gerych ⋅ Sana Tonekaboni ⋅ Anna Goldenberg ⋅ Berk Ustun ⋅ Tom Hartvigsen
9:17 AM
PaPaGei: Open Foundation Models for Optical Physiological Signals
Arvind Pillai ⋅ Dimitrios Spathis ⋅ Fahim Kawsar ⋅ Mohammad Malekzadeh
9:29 AM
TimeSeriesExam: A Time Series Understanding Exam
Yifu Cai ⋅ Arjun Choudhry ⋅ Mononito Goswami ⋅ Artur Dubrawski
11:10 AM
TimePFN: Effective Multivariate Time Series Forecasting with Synthetic Data
Ege Onur Taga ⋅ Muhammed Emrullah Ildiz ⋅ Samet Oymak
12:00 PM
Lunch Break
2:35 PM
Towards Time-Series Reasoning with LLMs
Winnie Chow ⋅ Lauren Gardiner ⋅ Haraldur Hallgrimsson ⋅ Maxwell Xu ⋅ Shirley Ren
2:47 PM
Benchmarking out-of-the-box forecasters of varying scales in biology
Anthony Culos ⋅ Mohammed AlQuraishi
2:53 PM
Coffee Break
3:30 PM
Scaling-laws for Large Time-series Models
JUSTIN ALSING ⋅ Thomas Edwards ⋅ Benjamin Wandelt ⋅ James Alvey ⋅ Nam Nguyen
3:42 PM
Towards Resolution-Aware Retrieval Augmented Zero-Shot Forecasting
Iman Deznabi ⋅ Peeyush Kumar ⋅ Madalina Fiterau
4:22 PM
Maven: A Multimodal Foundation Model for Supernova Science
Gemma Zhang ⋅ Thomas Helfer ⋅ Alex Gagliano ⋅ Siddharth Mishra-Sharma ⋅ V Villar
4:34 PM
Mamba4Cast: Efficient Zero-Shot Time Series Forecasting with State Space Models
Sathya Kamesh Bhethanabhotla ⋅ Omar Swelam ⋅ Julien Siems ⋅ David Salinas ⋅ Frank Hutter
5:14 PM
Closing Remarks
Masking the Gaps: An Imputation-Free Approach to Time Series Modeling with Missing Data
Abhilash Neog ⋅ Arka Daw ⋅ Sepideh Fatemi Khorasgani ⋅ Anuj Karpatne
MEDS-torch: An ML Pipleine for Inductive Experiments for EHR Medical Foundation Models
Nassim Oufattole ⋅ Teya Bergamaschi ⋅ Pawel Renc ⋅ Aleksia Kolo ⋅ Matthew McDermott ⋅ Collin Stultz
Efficient Time Series Processing for Transformers and State-Space Models through Token Merging
Leon Götz ⋅ Marcel Kollovieh ⋅ Stephan Günnemann ⋅ Leo Schwinn
Towards Large-scale Clinical Multi-variate Time-series Datasets
Manuel 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
Scaling to Billion Parameters for Time Series Foundation Models with Mixture of Experts
Xiaoming Shi ⋅ Shiyu Wang ⋅ Yuqi Nie ⋅ Dianqi Li ⋅ Zhou Ye ⋅ Qingsong Wen ⋅ Ming Jin
LETS-C: Leveraging Text Embedding for Time Series Classification
Rachneet Kaur ⋅ Zhen Zeng ⋅ Tucker Balch ⋅ Manuela Veloso
Unveiling and Manipulating Concepts in Time Series Foundation Models
Michal Wilinski ⋅ Mononito Goswami ⋅ Nina Żukowska ⋅ Willa Potosnak ⋅ Artur Dubrawski
From RNNs to Foundation Models: An Empirical Study on Commercial Building Energy Consumption
Shourya Bose ⋅ Yijiang Li ⋅ Amy Van Sant ⋅ Yu Zhang ⋅ Kibaek Kim
♠ SPADE ♠ Split Peak Attention DEcomposition
Malcolm Wolff ⋅ Kin Gutierrez ⋅ Boris Oreshkin ⋅ Sunny Ruan ⋅ Sitan Yang ⋅ Abhinav Katoch ⋅ Shankar Ramasubramanian ⋅ Youxin Zhang ⋅ Michael Mahoney ⋅ Dmitry Efimov ⋅ Vincent Quenneville-Belair
TrajGPT: Healthcare Time-Series Representation Learning for Trajectory Prediction
Ziyang Song ⋅ Qincheng Lu ⋅ Mike He Zhu ⋅ David Buckeridge ⋅ Yue Li
Test-Time Learning For Time Series Forecasting
Panayiotis Christou ⋅ Shichu Chen ⋅ Xupeng Chen ⋅ Parijat Dube
Unveiling the Potential of Text in High-Dimensional Time Series Forecasting
Xin Zhou ⋅ Weiqing Wang ⋅ SHILIN QU ⋅ Zhiqiang Zhang ⋅ Christoph Bergmeir
LiMTR: Time Series Motion Prediction for Diverse Road Users through Multimodal Feature Integration
Camiel Oerlemans ⋅ Bram Grooten ⋅ Michiel Braat ⋅ Alaa Alassi ⋅ Emilia Silvas ⋅ Decebal Constantin Mocanu
Effectively Leveraging Exogenous Information across Neural Forecasters
Andres Potapczynski ⋅ Kin Gutierrez ⋅ Malcolm Wolff ⋅ Andrew Wilson ⋅ Dmitry Efimov ⋅ Vincent Quenneville-Belair
Transformer-based Time-Series Biomarker Discovery for COPD Diagnosis
Soham Gadgil ⋅ Joshua Galanter ⋅ Mohammadreza Negahdar
Probabilistic Forecasting for Building Energy Systems: Are Time-Series Foundation Models the Answer?
Young-Jin Park ⋅ François Germain ⋅ Jing Liu ⋅ Ye Wang ⋅ Gordon Wichern ⋅ Toshiaki Koike-Akino ⋅ Navid Azizan ⋅ Christopher Laughman ⋅ Ankush Chakrabarty
Reimagining Time Series Foundation Models: Metadata and State-Space Model Perspectives
Pengrui Quan ⋅ Ozan Mulayim ⋅ Liying Han ⋅ Dezhi Hong ⋅ Mario Berges ⋅ Mani Srivastava
When Larger Isn’t Better: Lightweight CNNs Outperform Large Time-Series Models in Classification of Oil and Gas Drilling Data
abdallah benzine ⋅ J.S. Buiting ⋅ Soumyadipta Sengupta ⋅ Badal Gupta ⋅ Youssef Tamaazousti
Do we really need Foundation Models for multi-step-ahead Epidemic Forecasting?
Mrinmoy Dey ⋅ Aprameyo Chakrabartty ⋅ Dhruv Sarkar ⋅ Tanujit Chakraborty
A Language Model-Guided Framework for Mining Time Series with Distributional Shifts
Haibei Zhu ⋅ Yousef El-Laham ⋅ Elizabeth Fons ⋅ Svitlana Vyetrenko
GIFT-Eval: A Benchmark for General Time Series Forecasting Model Evaluation
Ibrahim Taha Aksu ⋅ Gerald Woo ⋅ Juncheng Liu ⋅ Xu Liu ⋅ Chenghao Liu ⋅ Silvio Savarese ⋅ Caiming Xiong ⋅ Doyen Sahoo
Enhancing Multivariate Time Series Forecasting via Multi-Task Learning and Random Matrix Theory
Romain Ilbert ⋅ Malik Tiomoko ⋅ Cosme Louart ⋅ Vasilii Feofanov ⋅ Themis Palpanas ⋅ Ievgen Redko
Context is Key: A Benchmark for Forecasting with Essential Textual Information
Arjun Ashok ⋅ Andrew Williams ⋅ Étienne Marcotte ⋅ Valentina Zantedeschi ⋅ Jithendaraa Subramanian ⋅ Roland Riachi ⋅ James Requeima ⋅ Alexandre Lacoste ⋅ Irina Rish ⋅ Nicolas Chapados ⋅ Alexandre Drouin
Weakly-supervised Multi-sensor Anomaly Detection with Time-series Foundation Models
Zelin He ⋅ Matthew Reimherr ⋅ Sarah Alnegheimish ⋅ Akash Chandrayan
UniTST: Effectively Modeling Inter-Series and Intra-Series Dependencies for Multivariate Time Series Forecasting
Juncheng Liu ⋅ Chenghao Liu ⋅ Gerald Woo ⋅ Yiwei Wang ⋅ Bryan Hooi ⋅ Caiming Xiong ⋅ Doyen Sahoo
Text2Freq: Learning Series Patterns from Text via Frequency Domain
Ming-Chih Lo ⋅ Ching Chang ⋅ Wen-Chih Peng
In-context Quantile Regression for Multi-product Inventory Management using Time-series Transformers
Magnus Josef Maichle ⋅ Sohom Mukherjee ⋅ Kai Michael Günder ⋅ Ivane Antonov ⋅ Nikolai Stein ⋅ Richard Pibernik
Implicit Reasoning in Deep Time Series Forecasting
Willa Potosnak ⋅ Cristian Challu ⋅ Mononito Goswami ⋅ Michal Wilinski ⋅ Nina Żukowska ⋅ Artur Dubrawski
Enhance Time Series Modeling by Integrating LLM
Can (Sam) Chen ⋅ Gabriel Oliveira ⋅ Hossein Sharifi-Noghabi ⋅ Tristan Sylvain
General-Purpose Brain Foundation Models for Time-Series Neuroimaging Data
Mohammad Javad Darvishi Bayazi ⋅ Hena Ghonia ⋅ Roland Riachi ⋅ Bruno Aristimunha ⋅ Arian Khorasani ⋅ Md Rifat Arefin ⋅ Amin Darabi ⋅ Guillaume Dumas ⋅ Irina Rish
Towards Long-Context Time Series Foundation Models
Nina Żukowska ⋅ Mononito Goswami ⋅ Michal Wilinski ⋅ Willa Potosnak ⋅ Artur Dubrawski
Joint Embedding go Temporal
Sofiane ENNADIR ⋅ Siavash Golkar ⋅ Leopoldo Sarra
Towards Unbiased Evaluation of Time-series Anomaly Detector
Debarpan Bhattacharya ⋅ Sumanta Mukherjee ⋅ Chandramouli Kamanchi ⋅ Vijay Ekambaram ⋅ Arindam Jati ⋅ Pankaj Dayama
Leveraging Periodicity for Robustness with Multi-modal Mood Pattern Models
Jaya Narain ⋅ Qinhua Sun ⋅ Oussama Elachqar ⋅ Haraldur Hallgrimsson ⋅ Feng Zhu ⋅ Shirley Ren
Sequential Order-Robust Mamba for Time Series Forecasting
Seunghan Lee ⋅ Juri Hong ⋅ Kibok Lee ⋅ Taeyoung Park
Align and Fine-Tune: Enhancing LLMs for Time-Series Forecasting
Ching Chang ⋅ Wei-Yao Wang ⋅ Wen-Chih Peng ⋅ Tien-Fu Chen ⋅ Sagar Samtani
LLMForecaster: Improving Seasonal Event Forecasts with Unstructured Textual Data
Hanyu Zhang ⋅ Chuck Arvin ⋅ Dmitry Efimov ⋅ Michael Mahoney ⋅ Dominique Perrault-Joncas ⋅ Shankar Ramasubramanian ⋅ Andrew Wilson ⋅ Malcolm Wolff
Mixture of Experts for Time Series Foundation Models
Xu Liu ⋅ Juncheng Liu ⋅ Gerald Woo ⋅ Ibrahim Taha Aksu ⋅ Chenghao Liu ⋅ Silvio Savarese ⋅ Caiming Xiong ⋅ Doyen Sahoo
Deep Temporal Deaggregation: Large-Scale Spatio-Temporal Generative Models
David Bergström ⋅ Mattias Tiger ⋅ Fredrik Heintz
Hierarchical Time Series Forecasting Via Latent Mean Encoding
Alessandro Salatiello ⋅ Stefan Birr ⋅ Manuel Kunz
PRIMUS: Pretraining IMU Encoders with Multimodal and Self-Supervised Learning
Arnav Das ⋅ Chi Ian Tang ⋅ Fahim Kawsar ⋅ Mohammad Malekzadeh
Stochastic Sparse Sampling: A Framework for Local Explainability in Variable-Length Medical Time Series
Xavier Mootoo ⋅ ALAN DIAZ-MONTIEL ⋅ Milad Lankarany ⋅ Hina Tabassum
Adaptive Information Routing for Multi Modal Time Series Forecasting
Jun Seo ⋅ Hyeokjun Choe ⋅ Seohui Bae ⋅ Soyeon Park ⋅ Jinseok Yang ⋅ Dongwan Kang ⋅ Woohyung Lim
Catching the Spikes: Heteroscedastic Uncertainty Quantification for Enhanced Malaria Prediction
Feng Chen ⋅ Qi Qi ⋅ Jiayu Qiu ⋅ Kemeng Zhang ⋅ Xiang Li
Electrocardiogram Report Generation and Question Answering via Retrieval-Augmented Self-Supervised Modeling
jialu tang ⋅ Tong Xia ⋅ Yuan Lu ⋅ Cecilia Mascolo ⋅ Aaqib Saeed