Elliot L. Epstein

According to our database, Elliot L. Epstein authored at least 9 papers between 2023 and 2026.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of four.

2026

Flash-SD-KDE: Accelerating SD-KDE with Tensor Cores.

Elliot L. Epstein, Rajat Vadiraj Dwaraknath, John Winnicki

CoRR, February, 2026

Allocate Marginal Reviews to Borderline Papers Using LLM Comparative Ranking.

Elliot L. Epstein, Rajat Vadiraj Dwaraknath, John Winnicki, Thanawat Sornwanee

CoRR, February, 2026

2025

LLMs are Overconfident: Evaluating Confidence Interval Calibration with FermiEval.

Elliot L. Epstein, John Winnicki, Thanawat Sornwanee, Rajat Vadiraj Dwaraknath

CoRR, October, 2025

A Set-Sequence Model for Time Series.

Elliot L. Epstein, Apaar Sadhwani, Kay Giesecke

CoRR, May, 2025

Score-Debiased Kernel Density Estimation.

Elliot L. Epstein, Rajat Vadiraj Dwaraknath, Thanawat Sornwanee, John Winnicki, Jerry Weihong Liu

CoRR, April, 2025

SD-KDE: Score-Debiased Kernel Density Estimation.

Elliot L. Epstein, Rajat Vadiraj Dwaraknath, Thanawat Sornwanee, John Winnicki, Jerry W. Liu

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Attention Factors for Statistical Arbitrage.

Elliot L. Epstein, Rose Wang, Jaewon Choi, Markus Pelger

Proceedings of the 6th ACM International Conference on AI in Finance, 2025

2024

MMMT-IF: A Challenging Multimodal Multi-Turn Instruction Following Benchmark.

Elliot L. Epstein, Kaisheng Yao, Jing Li, Xinyi Bai, Hamid Palangi

CoRR, 2024

2023

Simple Hardware-Efficient Long Convolutions for Sequence Modeling.

Daniel Y. Fu, Elliot L. Epstein, Eric Nguyen, Armin W. Thomas, Michael Zhang, Tri Dao, Atri Rudra, Christopher Ré

Proceedings of the International Conference on Machine Learning, 2023