activity
20222025
most citedFirst De-Trend then Attend: Rethinking Attention for Time-Series Forecasting

23 citations · 25 across the 5 of their papers we have counts for

collaborators

5 papers

cs.AI2025★ 2 cited

The Amazon Nova Family of Models: Technical Report and Model Card

Amazon AGI, Aaron Langford, Aayush Shah +783

We present Amazon Nova, a new generation of state-of-the-art foundation models that deliver frontier intelligence and industry-leading price performance. Amazon Nova Pro is a highl…

cs.LG2024

Collage: Light-Weight Low-Precision Strategy for LLM Training

Tao Yu, Gaurav Gupta, Karthick Gopalswamy +7

Large models training is plagued by the intense compute cost and limited hardware memory. A practical solution is low-precision representation but is troubled by loss in numerical…

cs.LG2023

Pessimistic Off-Policy Multi-Objective Optimization

Shima Alizadeh, Aniruddha Bhargava, Karthick Gopalswamy +3

Multi-objective optimization is a type of decision making problems where multiple conflicting objectives are optimized. We study offline optimization of multi-objective policies fr…

cs.LG2023

Cross-Frequency Time Series Meta-Forecasting

Mike Van Ness, Huibin Shen, Hao Wang +3

Meta-forecasting is a newly emerging field which combines meta-learning and time series forecasting. The goal of meta-forecasting is to train over a collection of source time serie…

cs.LG2022★ 23 cited

First De-Trend then Attend: Rethinking Attention for Time-Series Forecasting

Xiyuan Zhang, Xiaoyong Jin, Karthick Gopalswamy +6

Transformer-based models have gained large popularity and demonstrated promising results in long-term time-series forecasting in recent years. In addition to learning attention in…