A5068572605- Machine Learning in Materials Science
- Computational Drug Discovery Methods
- Protein Structure and Dynamics
- Advanced Chemical Physics Studies
- Advanced Image Processing Techniques
- Image Enhancement Techniques
- Functional Equations Stability Results
- Image and Signal Denoising Methods
Microsoft Research Asia (China)
2022-2024
Abstract Advances in deep learning have greatly improved structure prediction of molecules. However, many macroscopic observations that are important for real-world applications not functions a single molecular but rather determined from the equilibrium distribution structures. Conventional methods obtaining these distributions, such as dynamics simulation, computationally expensive and often intractable. Here we introduce framework, called Distributional Graphormer (DiG), an attempt to...
This note is intended for expanding the details on derivation and properties of density functional theory, in hope to make them more systematic, better motivated, step-by-step readers new domain. The starts with basic concepts quantum mechanics, then takes step towards many-body systems using tools second quantization Fock space, some highlights Coulomb system. Given these general technical preparations, Hartree-Fock method naturally unrolled, expressions various cases quantities. Density...
Orbital-free density functional theory (OFDFT) is a quantum chemistry formulation that has lower cost scaling than the prevailing Kohn-Sham DFT, which increasingly desired for contemporary molecular research. However, its accuracy limited by kinetic energy functional, notoriously hard to approximate non-periodic systems. Here we propose M-OFDFT, an OFDFT approach capable of solving systems using deep learning model. We build essential non-locality into model, made affordable concise...