Mass tensor molecular dynamics

By Charles H. Bennett. 1975

Subfields: Natural Language Processing, Computational Chemistry & Drug Discovery

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The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Natural Language Processing

1. Jascha Narain Sohl-Dickstein
2. Daniel Lévy
3. Radford M. Neal
4. Matthew D. Hoffman

In Computational Chemistry & Drug Discovery

1. Jascha Narain Sohl-Dickstein
2. Daniel Lévy
3. Radford M. Neal
4. Matthew D. Hoffman

Citations in the corpus

• Generalizing Hamiltonian Monte Carlo with Neural Networks (2017, methodology): “It is further capable of emulating several common extensions of HMC such as withintrajectory tempering (Neal, 1996) and diagonal mass matrices (Bennett, 1975).”
• Handbook of Markov Chain Monte Carlo (2011, neutral): “Using such a kinetic energy function to compensate for correlations between position variables has a long history in molecular dynamics (Bennett, 1975).”
• MCMC Using Hamiltonian Dynamics (2011, background): “ch gives K(p′) = (p′)TM′−1p′ with M′ = (L−1(LLT)(L−1)T)−1 = I. Using such a kinetic energy function to compensate for correlations between position variables has a long history in molecular dynamics (Bennett, 1975). The usefulness of this technique is limited by the computational cost of matrix oper”