11 papers · ranked by Valyu relevance
Jun Mai, Bangyan Liao, Zhenjun Zhao, Yingping Zeng + 5 more
The Homotopy paradigm, a general principle for solving challenging problems, appears across diverse domains such as robust optimization, global optimization, polynomial root-finding, and sampling. Practical solvers for these problems typically follow a predictor-corrector (PC) structure, but rely on hand-crafted…
Muhammad Bilal Shahid, Prajwal Koirla, Cody Fleming
Learned time-series models, whether continuous- or discrete-time, are widely used to forecast the states of a dynamical system. Such models generate multi-step forecasts either directly, by predicting the full horizon at once, or iteratively, by feeding back their own predictions at each step. In both cases, the…
Subha Maity, Debarghya Mukherjee, Moulinath Banerjee, Yuekai Sun
Time-varying stochastic optimization problems frequently arise in machine learning practice (e.g. gradual domain shift, object tracking, strategic classification). Often, the underlying process that drives the distribution shift is continuous in nature. We exploit this underlying continuity by developing…
Bei Li, Tong Zheng, Ruikang K. Wang, Jiahao Liu + 7 more
Average Coefficient Learning Authors: ['Bei Li' 'Tong Zheng' 'Ruikang K. Wang' 'Jiahao Liu' 'Qingyan Guo' 'Junliang Guo' 'Xu Tan' 'Tong Xiao' 'Jingbo Zhu' 'Jingang Wang' 'Xunliang Cai'] Residual networks, as discrete approximations of Ordinary Differential Equations (ODEs), have inspired significant advancements in…
Panagiotis Chrysinas, Changyou Chen, Rudiyanto Gunawan
Predicting the cell response to chemical compounds is central to drug discovery, drug repurposing, and personalized medicine. To this end, large datasets of drug response signatures have been curated, most notably the Connectivity Map (CMap) from the Library of Integrated Network-based Cellular Signatures (LINCS)…
Yuta Hirabayashi, Daisuke Matsuoka
- A mesoscale weather prediction model that combines Swin-Unet is proposed as a deterministic Predictor and a diffusion model as a probabilistic Corrector. - Both the Predictor and Corrector were trained independently, enabling flexible updates to the deterministic Predictor without retraining the Corrector. - The…
Linde Schoenmaker, Olivier Béquignon, Willem Jespers, Gerard van Westen
Generative deep learning models have emerged as a powerful approach for de novo drug design, as they aid researchers in finding new molecules with desired properties. Despite continuous improvements in the field, a subset of the outputs that sequence-based de novo generators produce cannot be progressed due to errors.…
Lu Hong, PJ Lamberson, Scott E Page
An increasing proportion of decisions, design choices, and predictions are being made by hybrid groups consisting of humans and artificial intelligence (AI). In this paper, we provide analytic foundations that explain the potential benefits of hybrid groups on predictive tasks, the primary use of AI. Our analysis…
Peter E. Midford, John Cadigan, Peter D. Karp
Operon prediction is a valuable component of microbial-genome annotation because operon organization can yield inferences about gene function, and because knowledge of operon structure can aid the interpretation of gene expression data. We present a number of improvements to the existing Pathway Tools operon predictor…
Sharaf Malebary, Shaista Rahman, Omar Barukab, Rehab Ash’ari + 2 more
Acetylation is the most important post-translation modification (PTM) in eukaryotes; it has manifold effects on the level of protein that transform an acetyl group from an acetyl coenzyme to a specific site on a polypeptide chain. Acetylation sites play many important roles, including regulating membrane protein…
Rasmus M. Borup, Nicolai Ree, Jan Jensen
Determining the pKa values of various C-H sites in organic molecules offers valuable insights for synthetic chemists in predicting reaction sites. As molecular complexity increases, this task becomes more challenging. This paper introduces pKalculator, a quantum chemical (QM)-based workflow for automatic computations…