I am a Visiting Researcher (Full-Time) at ServiceNow Research, Montreal and a PhD Student at MILA in Irina Rish's group. At ServiceNow, I work with Étienne Marcotte, Alexandre Drouin, Valentina Zantedeschi and Nicolas Chapados. My current research interests are in time-series forecasting and decision making. I previously worked in computer vision and natural language processing.
My email address is arjun.ashok.psg [at] gmail [dot] com.
|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.|