2 citations · 4 across the 5 of their papers we have counts for
6 papers
Generative Pseudo-Force Fields for Molecular Generation
Stefaan Simon Pierre Hessmann, Khaled Kahouli, Stefan Gugler +4
Generating stable molecular conformations typically forces a tradeoff between the physical realism of energy-based relaxation and the sampling efficiency of data-driven generative…
Learning Hamiltonian Flow Maps: Mean Flow Consistency for Large-Timestep Molecular Dynamics
Winfried Ripken, Michael Plainer, Gregor Lied +5
Simulating the long-time evolution of Hamiltonian systems is limited by the small timesteps required for stable numerical integration. To overcome this constraint, we introduce a f…
Consistent Sampling and Simulation: Molecular Dynamics with Energy-Based Diffusion Models
Michael Plainer, Hao Wu, Leon Klein +2
In recent years, diffusion models trained on equilibrium molecular distributions have proven effective for sampling biomolecules. Beyond direct sampling, the score of such a model…
Doob's Lagrangian: A Sample-Efficient Variational Approach to Transition Path Sampling
Yuanqi Du, Michael Plainer, Rob Brekelmans +5
Rare event sampling in dynamical systems is a fundamental problem arising in the natural sciences, which poses significant computational challenges due to an exponentially large sp…
Transition Path Sampling with Boltzmann Generator-based MCMC Moves
Michael Plainer, Hannes Stärk, Charlotte Bunne +1
Sampling all possible transition paths between two 3D states of a molecular system has various applications ranging from catalyst design to drug discovery. Current approaches to sa…
Transporting Densities Across Dimensions
Michael Plainer, Felix Dietrich, Ioannis G. Kevrekidis
Even the best scientific equipment can only partially observe reality. Recorded data is often lower-dimensional, e.g., two-dimensional pictures of the three-dimensional world. Comb…