3 papers
cs.LG2021
Deep metric learning improves lab of origin prediction of genetically engineered plasmids
Igor M. Soares, Fernando H. F. Camargo, Adriano Marques +1
Genome engineering is undergoing unprecedented development and is now becoming widely available. To ensure responsible biotechnology innovation and to reduce misuse of engineered D…
cs.LG2021
Ranking labs-of-origin for genetically engineered DNA using Metric Learning
I. Muniz, F. H. F. Camargo, A. Marques
With the constant advancements of genetic engineering, a common concern is to be able to identify the lab-of-origin of genetically engineered DNA sequences. For that reason, AltLab…
cs.IR2020
MARS-Gym: A Gym framework to model, train, and evaluate Recommender Systems for Marketplaces
Marlesson R. O. Santana, Luckeciano C. Melo, Fernando H. F. Camargo +4
Recommender Systems are especially challenging for marketplaces since they must maximize user satisfaction while maintaining the healthiness and fairness of such ecosystems. In thi…