Machine-learning models can speed up the discovery of new materials by making predictions and suggesting experiments. But most models today only consider a few specific types of data or variables.

Abstract: Understanding the relationship between cognitive load and affective state in remote work is vital for designing intuitive collaboration. We present CoAffinity, a multimodal dataset ...

Abstract: Estimating electricity consumption accurately is essential for the planning and operation of energy systems, as well as for billing processes. Standard Load Profiles (SLP) are widely used to ...

OGBench is a benchmark designed to facilitate algorithms research in offline goal-conditioned reinforcement learning (RL), offline unsupervised RL, and offline RL. See the project page for videos and ...

Model2Vec is a technique to turn any sentence transformer into a really small static model, reducing model size by a factor up to 50 and making the models up to 500 times faster, with a small drop in ...