Thrilled to share that this survey on graph reduction has been accepted to #IJCAI2024. Do not miss this work if you hope to properly simplify your graph/network data! Look forward to meeting you in South Korea!

🚨 Call for Workshop Papers - Epidemiology meets Data at #KDD2024 🚨 Submit your work to the "Epidemiology meets Data" workshop epiDAMIK Workshop, short and full papers! 📆 Make sure to submit by May 28! #ML #AI #DataScience #PublicHealth #epidemiology epidamik.github.io

Check out the multiple Ph.D. and postdoc positions available at NingLab (We are hiring Ph.D. students & postdocs) at OSU. OSU NLP Group and NingLab (We are hiring Ph.D. students & postdocs) are long-term collaborators on LLMs for Chemistry and Biomedicine. Consider joining OSU! Retweet appreciated! 🙏🤝

Reminder to submit your work to epiDAMIK, the KDD workshop on epidemiology meets data!! The deadline has been extended to June 4, 2024.

Wonderful, many congratulations Jiaming Cui! Looking forward to exciting things from you at Virginia Tech Computer Science! Will soon miss you here GaTech CSE Georgia Tech Computing 👏🎊

1/2 Thrilled to share that our work "Time-Series Forecasting for Out-of-Distribution Generalization Using Invariant Learning" will appear in #ICML2024. Thanks to my advisor B. Aditya Prakash and collaborators Chao Zhang Harsha Kamarthi Zhiyuan (Leo) Zhao. Let us meet in Vienna! GaTech CSE

2/2 In this paper, we develop FOIL a new framework to alleviate the inherent out-of-distribution problem in time-series forecasting via invariant learning. Paper: arxiv.org/abs/2406.09130 Repo: github.com/AdityaLab/FOIL

Enjoying the stimulating interdisciplinary discussions under the sun at the beautiful National Academy of Engineering The Beckman Center Fantastic artwork in the building too #CAFOE GaTech CSE Georgia Tech Computing

Meet the Georgia Tech experts who are helping unlock the future of #AI. These experts will share their latest research findings in machine learning on the world stage at ICML Conference (July 21-27). Tech experts are part of 40 teams with new research, and the institute is the lead

School of CSE researchers co-author one-fifth of all Georgia Tech papers presented next week at #ICML2024! Check out the GT @ ICML website for abstracts of all papers, plus two feature highlights of CSE research! sites.gatech.edu/research/icml-… Georgia Tech Computing Georgia Tech Research Machine Learning at Georgia Tech

Catch Haoxin ICML Conference 2024 in Vienna, presenting our work on out of distribution generalization (OOD) in time-series forecasting. Get OOD robustness for *any* forecasting method via invariant learning using FOIL, our new model agnostic framework! github.com/AdityaLab/FOIL GaTech CSE

Our new paper ACL 2025 on LLMs for time series forecasting (TSF)! We propose LSTPrompt, a new way for prompting for zero-shot TSF tasks. Main idea: split TSF into short+long-term sub-tasks, tailoring prompts to each & guide LLMs to adapt GaTech CSE Machine Learning at Georgia Tech github.com/AdityaLab/lstp…

#KDD2024 is just around the corner! We are excited to share details about our upcoming tutorial on **Graph Neural Networks in Epidemic Modeling**: 📅 Date: Sunday, August 25 🕙 Time: 10:00 AM - 1:00 PM (Barcelona Time) 📍 Location: Room 119 Website: kdd2024epidemic.github.io

Awesome, many congratulations Alexander Rodríguez on the award - very well deserved! 🙌 🎉 🎊 And nice pic :-) #proudadvisor cc Georgia Tech Computing GaTech CSE Vivek Sarkar Machine Learning at Georgia Tech