Authors
Citations
- Collective Monte Carlo Updating for Spin Systems
- An overview of spatial microscopic and accelerated kinetic Monte Carlo methods
- Time-Dependent Statistics of the Ising Model
- Correlation length of the two-dimensional Ising spin glass with bimodal interactions
- Nonuniversal critical dynamics in Monte Carlo simulations
- The Ising Model for Population Biology
- Beitrag zur Theorie des Ferromagnetismus
- Crystal Statistics. I. A Two-Dimensional Model with an Order-Disorder Transition
- Magnetic correlations in two-dimensional spin-glasses
- Critical behaviour of the phase transition in the 2D Ising Model with impurities
- Toward an Ising model of cancer and beyond
- Enzymatic hydroxylation of an unactivated methylene C–H bond guided by molecular dynamics simulations
- Discovery of a regioselectivity switch in nitrating P450s guided by molecular dynamics simulations and Markov models
- Learning thermodynamics with Boltzmann machines
- First-principles prediction of the stacking fault energy of gold at finite temperature
- Bimodal Ising spin glass in two dimensions: The anomalous dimension η
- Accelerating Science with Generative Adversarial Networks: An Application to 3D Particle Showers in Multilayer Calorimeters
- Orientational phase behavior of polymer-grafted nanocubes
- Graph neural network based coarse-grained mapping prediction
- A modified Ising model of Barabási–Albert network with gene-type spins
- Unsupervised Learning-Based Multiscale Model of Thermochemistry in 1,3,5-Trinitro-1,3,5-triazinane (RDX)
- Generative adversarial networks
- Deep learning on the 2-dimensional Ising model to extract the crossover region with a variational autoencoder
- Generative adversarial networks (GAN) based efficient sampling of chemical composition space for inverse design of inorganic materials
- Molecular Dynamics Simulations in Drug Discovery and Pharmaceutical Development
- Predicting long- and short-range order with restricted Boltzmann machine
- Neural network reactive force field for C, H, N, and O systems
- Physics-informed machine learning
- Parsimonious neural networks learn interpretable physical laws
- Highly accurate protein structure prediction with AlphaFold
- Reconfigurable Chirality of DNA-Bridged Nanorod Dimers
- An Introduction to the Ising Model
- Ising granularity image analysis on VAE–GAN
- A universal graph deep learning interatomic potential for the periodic table
- Mapping microstructure to shock-induced temperature fields using deep learning
- Scaling deep learning for materials discovery
- Sampling with flows, diffusion, and autoregressive neural networks from a spin-glass perspective