Publications
The research team at Abacus.AI makes fundamental contributions to the field of AI/ML that might have an
impact in the short or long run and does applied research that has benefits in practice.
The areas we have been focusing on include large language models, time-series forecasting, recommender systems, automated machine learning, meta-learning, deep learning for tabular data, deep learning optimization, and fairness/debiasing in deep learning.
The team already has an impressive list of publications in top-tier conferences and workshops in
just over four years of its conception.
Duncan McElfresh, Sujay Khandagale, Jonathan Valverde, John Dickerson, Colin White
Workshop at AutoML-Conf 2022
Arjun Krishnakumar, Colin White, Arber Zela, Renbo Tu, Mahmoud Safari, Frank Hutter
NeurIPS Datasets Track 2022
Yang Liu, Sujay Khandagale, Colin White, Willie Neiswanger
NeurIPS Datasets Track 2021
Colin White, Willie Neiswanger, Sam Nolen, Yash Savani
Selected for spotlight presentation | NeurIPS 2020
Manley Roberts, Himanshu Thakur, Christine Herlihy, Colin White, Samuel Dooley
NeurIPS Workshop, I Can't Believe It's Not Better: Failure Modes in the Age of Foundation Models, 2023
Gurnoor Khurana, Samuel Dooley, Siddartha Naidu, Colin White
ICLR Workshop on Practical ML for Developing Countries, 2023
Vishak Prasad, Colin White, Paarth Jain, Sibasis Nayak, Rishabh Iyer, Ganesh Ramakrishnan
Workshop at AutoML-Conf 2022
Colin White, Willie Neiswanger, Yash Savani
NeurIPS Workshop on Bayesian Deep Learning 2019
Naveen Sundar Govindarajulu and Colin White
NeurIPS Workshop on Robust AI in Financial Services, 2019
Naveen Sundar Govindarajulu and Colin White
NeurIPS Workshop on Knowledge Representation to ML, 2019
Forecasting and Planning
Anomaly Detection
Language AI
Personalization AI
Marketing and Sales AI
Foundation Models
Vision AI
Fraud and Security