MatSciBERT: A materials domain language model for text mining and information extraction

T Gupta, M Zaki, NMA Krishnan, Mausam - npj Computational Materials, 2022 - nature.com
A large amount of materials science knowledge is generated and stored as text published in
peer-reviewed scientific literature. While recent developments in natural language …

DeepEthogram, a machine learning pipeline for supervised behavior classification from raw pixels

JP Bohnslav, NK Wimalasena, KJ Clausing, YY Dai… - elife, 2021 - elifesciences.org
Videos of animal behavior are used to quantify researcher-defined behaviors of interest to
study neural function, gene mutations, and pharmacological therapies. Behaviors of interest …

Distributional preference learning: Understanding and accounting for hidden context in rlhf

A Siththaranjan, C Laidlaw… - ar** molecular therapies require deciphering the
cell types in which proteins act as well as the interactions between proteins. However …

Fully automated, semantic segmentation of whole-body 18F-FDG PET/CT images based on data-centric artificial intelligence

LKS Sundar, J Yu, O Muzik, OC Kulterer… - Journal of Nuclear …, 2022 - jnm.snmjournals.org
We introduce multiple-organ objective segmentation (MOOSE) software that generates
subject-specific, multiorgan segmentation using data-centric artificial intelligence principles …

[PDF][PDF] Deep Polarized Network for Supervised Learning of Accurate Binary Hashing Codes.

L Fan, KW Ng, C Ju, T Zhang, CS Chan - IJCAI, 2020 - ijcai.org
This paper proposes a novel deep polarized network (DPN) for learning to hash, in which
each channel in the network outputs is pushed far away from zero by employing a …