State-of-the-art computer vision systems are trained to predict a fixed set of predetermined
object categories. This restricted form of supervision limits their generality and usability since …

Contrastive models like CLIP have been shown to learn robust representations of images that
capture both semantics and style. To leverage these representations for image generation, …

In this work various methods of using vegetable oil (Jatropha oil) and methanol such as
blending, transesterification and dual fuel operation were studied experimentally. A single …

Polycyclic aromatic hydrocarbons (PAHs) are a family of toxicants that are ubiquitous in the
environment. These contaminants generate considerable interest, because some of them are …

Herbal medicines have long been used as a traditional mode of therapy for various ailments
in India. They are being used increasingly as dietary supplements to ward off common …

Recognition of the need for evidence-based interventions to help to improve the effectiveness
and efficiency of humanitarian responses has been increasing. However, little is known …

We demonstrate that scaling up language models greatly improves task-agnostic, few-shot
performance, sometimes even becoming competitive with prior state-of-the-art fine-tuning …

Text-to-image generation has traditionally focused on finding better modeling assumptions
for training on a fixed dataset. These assumptions might involve complex architectures, …

Diffusion models have recently been shown to generate high-quality synthetic images,
especially when paired with a guidance technique to trade off diversity for fidelity. We explore …

Activated carbon prepared from Ceiba pentandra hulls, an agricultural solid waste by-product,
for the removal of copper and cadmium from aqueous solutions has been studied. …