Publications (7)
Quantum Machine Learning in Drug Discovery: Applications in Academia and Pharmaceutical Industries
Anthony M. Smaldone, Yu Shee, Gregory W. Kyro +8
The nexus of quantum computing and machine learning - quantum machine learning - offers the potential for significant advancements in chemistry. This review specifically explores t…
Kernel-Elastic Autoencoder for Molecular Design
Haote Li, Yu Shee, Brandon Allen +2
We introduce the Kernel-Elastic Autoencoder (KAE), a self-supervised generative model based on the transformer architecture with enhanced performance for molecular design. KAE is f…
DirectMultiStep: Direct Route Generation for Multistep Retrosynthesis
Yu Shee, Anton Morgunov, Haote Li +1
Traditional computer-aided synthesis planning (CASP) methods rely on iterative single-step predictions, leading to exponential search space growth that limits efficiency and scalab…
Qubit-efficient encoding scheme for quantum simulations of electronic structure
Yu Shee, Pei-Kai Tsai, Cheng-Lin Hong +2
Simulating electronic structure on a quantum computer requires encoding of fermionic systems onto qubits. Common encoding methods transform a fermionic system of spin-orbitals…
FragmentRetro: A Quadratic Retrosynthetic Method Based on Fragmentation Algorithms
Yu Shee, Anthony M. Smaldone, Anton Morgunov +2
Retrosynthesis, the process of deconstructing a target molecule into simpler precursors, is crucial for computer-aided synthesis planning (CASP). Widely adopted tree-search methods…
Quantum Simulation of Preferred Tautomeric State Prediction
Yu Shee, Tzu-Lan Yeh, Jen-Yueh Hsiao +3
Prediction of tautomers plays an essential role in computer-aided drug discovery. However, it remains a challenging task nowadays to accurately predict the canonical tautomeric for…