activity
20172025
most citedObjective-Reinforced Generative Adversarial Networks (ORGAN) for Sequence Generation Models

493 citations · 884 across the 5 of their papers we have counts for

collaborators

5 papers

cond-mat.mtrl-sci2025★ 1 cited

EGMOF: Efficient Generation of Metal-Organic Frameworks Using a Hybrid Diffusion-Transformer Architecture

Seunghee Han, Yeonghun Kang, Taeun Bae +5

Designing materials with targeted properties remains challenging due to the vastness of chemical space and the scarcity of property-labeled data. While recent advances in generativ…

quant-ph2022★ 88 cited

Exploring the Advantages of Quantum Generative Adversarial Networks in Generative Chemistry

Po-Yu Kao, Ya-Chu Yang, Wei-Yin Chiang +8

De novo drug design with desired biological activities is crucial for developing novel therapeutics for patients. The drug development process is time and resource-consuming, and i…

quant-ph2021★ 234 cited

A Quantum Computing View on Unitary Coupled Cluster Theory

Abhinav Anand, Philipp Schleich, Sumner Alperin-Lea +7

We present a review of the Unitary Coupled Cluster (UCC) ansatz and related ansätze which are used to variationally solve the electronic structure problem on quantum computers. A b…

quant-ph2020★ 68 cited

Tequila: A platform for rapid development of quantum algorithms

Jakob S. Kottmann, Sumner Alperin-Lea, Teresa Tamayo-Mendoza +15

Variational quantum algorithms are currently the most promising class of algorithms for deployment on near-term quantum computers. In contrast to classical algorithms, there are al…

stat.ML2017★ 493 cited

Objective-Reinforced Generative Adversarial Networks (ORGAN) for Sequence Generation Models

Gabriel Lima Guimaraes, Benjamin Sanchez-Lengeling, Carlos Outeiral +2

In unsupervised data generation tasks, besides the generation of a sample based on previous observations, one would often like to give hints to the model in order to bias the gener…