no code implementations • 27 Feb 2024 • Michael Celentano, William S. DeWitt, Sebastian Prillo, Yun S. Song
Consequently, the computational cost is determined not by the size of the final simulated tree, but by the size of the population tree in which it is embedded.
no code implementations • 21 May 2021 • Jeffrey Chan, Aldo Pacchiano, Nilesh Tripuraneni, Yun S. Song, Peter Bartlett, Michael I. Jordan
Standard approaches to decision-making under uncertainty focus on sequential exploration of the space of decisions.
no code implementations • ICLR Workshop EBM 2021 • Nick Bhattacharya, Neil Thomas, Roshan Rao, Justas Daupras, Peter K Koo, David Baker, Yun S. Song, Sergey Ovchinnikov
On the one hand, factored attention is a direct simplification of multihead scaled dot-product attention in the Transformer.
5 code implementations • NeurIPS 2019 • Roshan Rao, Nicholas Bhattacharya, Neil Thomas, Yan Duan, Xi Chen, John Canny, Pieter Abbeel, Yun S. Song
Semi-supervised learning has emerged as an important paradigm in protein modeling due to the high cost of acquiring supervised protein labels, but the current literature is fragmented when it comes to datasets and standardized evaluation techniques.
1 code implementation • NeurIPS 2018 • Jeffrey Chan, Valerio Perrone, Jeffrey P. Spence, Paul A. Jenkins, Sara Mathieson, Yun S. Song
To achieve this, two inferential challenges need to be addressed: (1) population data are exchangeable, calling for methods that efficiently exploit the symmetries of the data, and (2) computing likelihoods is intractable as it requires integrating over a set of correlated, extremely high-dimensional latent variables.
no code implementations • 12 Dec 2016 • Miaoyan Wang, Yun S. Song
Tensor decompositions have rich applications in statistics and machine learning, and developing efficient, accurate algorithms for the problem has received much attention recently.