I am a Visiting Researcher (Full-Time) at ServiceNow Research, Montreal, Canada and a PhD student at MILA-Quebec AI Institute and Université de Montréal advised by Irina Rish and Alexandre Drouin. My research interests are in time series forecasting.
My email address is arjun.ashok [at] servicenow [dot] com. Email me if you'd like to connect, be it about research or music or anything else!
I am looking to supervise motivated undergraduate and masters students on problems related to large time series models. Reach out at my email if you're interested.
Nov '24 | Gave an oral presentation on Context is Key at the Workshop on Foundation Models for Time Series: Exploring New Frontiers co-located with ACM ICAIF 2024, New York, USA. |
Oct '24 | Paper on natural-language based context-aware forecasting, Context is Key: A Benchmark for Forecasting with Essential Textual Information, is out on arXiv. |
Sep '24 | Co-organizing the The first NeurIPS workshop on Time Series in the Age of Large Models at NeurIPS 2024 in December. Consider participating! |
July '24 | Gave an invited talk on Natural Language based Context-Aware Forecasting at the International Symposium on Forecasting (ISF) 2024. |
May '24 | Presented TACTiS-2 at ICLR 2024. TACTiS-2 is a highly flexible model for multivariate probabilistic time series prediction tasks. Check out the tweet thread and poster here! |
Feb '24 | The full version of Lag-Llama released with open-source model checkpoints! Check the announcement here! |
Jan '24 | I gave a talk on our efforts Towards General-Purpose Models for Time-Series Prediction at the Winter 2024 Montreal Time Series Meetup. |
Jan '24 | TACTiS-2 accepted at ICLR 2024! |
Dec '23 | I gave a talk on Building Foundation Models for Time Series Data at the 6th workshop on Neural Scaling Laws co-located with NeurIPS 2023. |
Oct '23 | TACTiS-2 is out on arXiv. |
Oct '23 | A preliminary version of Lag-Llama is out on arXiv. |
Jan '23 | One paper on out-of-distribution detection accepted to ICLR 2023. This is work in collaboration with folks at ML Collective mentored by Rosanne Liu. |
Jan '23 | Started as a Visiting Researcher (Full-Time) at ServiceNow Research, Montreal. Excited to continue working on problems in time series representation learning! |
Aug '22 | Preliminary work on self-supervised learning objectives for weather time series accepted at the AAAI 2022 Fall Symposium on Climate Change. |
Jul '22 | One paper on Class-Incremental Learning accepted as a full paper at ECCV 2022. |
Jun '22 | Started as a Research Intern at IBM Research, India. I'll be working on building self-supervised learning objectives and pre-trained models for geospatial weather time series. |
Jun '22 | One paper on cross-task generalization in NLP submitted to EMNLP 2022 (Update: Accepted). |
Apr '22 | One paper on Class-Incremental Learning accepted at the CLVISION Workshop at CVPR 2022 as a non-archival paper (Update: Accepted at ECCV 2022). |
Apr '22 | One reproducibility report on Self-Supervision and Few-shot Learning accepted at the ML Reproducibility Challenge 2021 (Fall Edition) and published at ReScience-C. |
Oct '21 | One paper on out-of-distribution generalization accepted as AAAI 2022 as a student abstract. |
Jun '21 | Started as a Research Assistant at IIT Hyderabad under Prof. Vineeth Balasubramanian. |
TL;DR Abstract arXiv Code Benchmark Visualization Tweet
TL;DR Abstract arXiv Code OpenReview Tweet Poster Blog 15-min Video
TL;DR Abstract Paper Code (1k+ ★) Weights Demo Tweet 15-min Video
I am a Carnatic Vocalist and a student of Vidwan Bharat Sundar. I have performed Carnatic concerts in multiple venues in India, and continue to perform in and around Montréal and Ottawa regularly. Here is a recording of a concert of mine from July 2024. |