1 code implementation • 8 Jan 2024 • Vijay Ekambaram, Arindam Jati, Nam H. Nguyen, Pankaj Dayama, Chandra Reddy, Wesley M. Gifford, Jayant Kalagnanam
Consequently, there has been a recent surge in utilizing pre-trained large language models (LLMs) with token adaptations for TS forecasting.
no code implementations • 31 Oct 2023 • Santosh Palaskar, Vijay Ekambaram, Arindam Jati, Neelamadhav Gantayat, Avirup Saha, Seema Nagar, Nam H. Nguyen, Pankaj Dayama, Renuka Sindhgatta, Prateeti Mohapatra, Harshit Kumar, Jayant Kalagnanam, Nandyala Hemachandra, Narayan Rangaraj
Business and IT Observability (BizITObs) data fuses both Biz-KPIs and IT event channels together as multivariate time series data.
1 code implementation • 14 Jun 2023 • Vijay Ekambaram, Arindam Jati, Nam Nguyen, Phanwadee Sinthong, Jayant Kalagnanam
TSMixer outperforms state-of-the-art MLP and Transformer models in forecasting by a considerable margin of 8-60%.
Ranked #1 on Time Series on ETTh1 (720) Multivariate
Multivariate Time Series Forecasting Representation Learning +2
no code implementations • 28 Nov 2022 • Arindam Jati, Vijay Ekambaram, Shaonli Pal, Brian Quanz, Wesley M. Gifford, Pavithra Harsha, Stuart Siegel, Sumanta Mukherjee, Chandra Narayanaswami
To address this test-validation mismatch, we propose a novel technique, H-Pro to drive HPO via test proxies by exploiting data hierarchies often associated with time series datasets.
1 code implementation • ACM SIGKDD International Conference on Knowledge Discovery & Data Mining 2020 • Vijay Ekambaram, Kushagra Manglik, Sumanta Mukherjee, SURYA SHRAVAN KUMAR SAJJA, Satyam Dwivedi, Vikas Raykar
Trend driven retail industries such as fashion, launch substantial new products every season.
Ranked #1 on New Product Sales Forecasting on VISUELLE2.0 (using extra training data)