Retrosynthesis aims to efficiently plan the synthesis of desirable chemicals by strategically
breaking down molecules into readily available building block compounds. Having a long …

The drug discovery process is a rigorous and time-consuming endeavor, typically requiring
several years of extensive research and development. Although classical machine learning …

Retrosynthesis prediction is crucial in organic synthesis and drug discovery, aiding chemists
in designing efficient synthetic routes for target molecules. Data-driven deep retrosynthesis …

Quantum computing promises to revolutionize our understanding of the limits of
computation, and its implications in cryptography have long been evident. Today …

Abstract Quantum Recurrent Neural Networks are receiving an increased attention thanks to
their enhanced generalization capabilities in time series analysis. However, their …

In the era of noisy intermediate-scale quantum (NISQ) computing, the synergistic
collaboration between quantum and classical computing models has emerged as a …

The high expenses imposed by current quantum cloud providers, coupled with the
escalating need for quantum resources, may incentivize the emergence of cheaper cloud …

The drug discovery process is a rigorous and time-consuming endeavor, typically requiring
several years of extensive research and development. Although classical machine learning …

Abstract According to American Society of Clinical Oncology, in 2020, around 300 thousand
people were diagnosed with brain or spinal cord tumor (s) worldwide. For effective treatment …

Quantum computing is a novel computational paradigm that promises substantial speed-ups
in a plethora of tasks that are computationally challenging for classical computers …