3 citations · 4 across the 12 of their papers we have counts for
9 papers · 1 filter
Joint Neural Posterior Estimation and Model Selection for Chemical Reaction Networks
J. Arturo Esquivel, Jorge A. Campos-Gonzalez-Angulo, Sergio Pablo-García +2
Simulation-based Bayesian inference for Chemical Reaction Networks (CRNs) must simultaneously solve two computationally demanding problems: discriminating between overlapping react…
Grand Canonical Generators
Andreas Burger, Malte Franke, Luka Mucko +2
We introduce Grand Canonical Generators (GCG), a generative framework that extends Boltzmann generators to the grand canonical ensemble. We present two designs. The first condition…
Colour me shocked: Exact Molecular Hessians from local MLIPs in O(N) time using sparse differentiation!
Luca Thiede, Andreas Burger, Alán Aspuru-Guzik
The Hessian of the energy with respect to the nuclear positions is indispensable in atomistic modelling. However, constructing this matrix requires Hessian vector products,…
From Global to Factor-Wise Expert Composition in Discrete Diffusion Models
Haozhe Huang, Yudong Xu, Abhijoy Mandal +1
Discrete diffusion models offer a powerful framework for solving complex reasoning tasks, particularly through compositional generation, which combines multiple pre-trained experts…
QPILOTS: Efficient Test-Time Q-Steering for Flow Policies
Yifan Ruan, Chenyang Cao, Andreas Burger +7
Flow-matching and diffusion policies are expressive action generators, but optimizing them with temporal-difference reinforcement learning (RL) remains difficult. Effective policy…
De novo molecular generation with optical property preconditioning at the token level
Haozhe Huang, Manuel Gonzalez Lastre, Hyun Suk Park +3
Designing OLED molecules with targeted optical properties remains challenging due to the scarcity of high-quality data and the limited reliability of conditional control in generat…
MōLe-Λ: Learning the Coupled-Cluster Response State for Energies, Gradients, and Properties
Andreas Burger, Luca Thiede, Abdulrahman Aldossary +4
Coupled-cluster (CC) theory is often considered the gold standard of quantum chemistry, but its high computational cost limits routine access to accurate energies, forces and respo…
Optimizing ground state preparation protocols with autoresearch
Luis Mantilla Calderón, Jérôme F. Gonthier, Ignacio Gustin +2
Artificial intelligent language-model based coding agents have significantly changed the way we interact with computers in our day-to-day, as it is common to use them to create, im…
Coupled Cluster con MōLe: Molecular Orbital Learning for Neural Wavefunctions
Luca Thiede, Abdulrahman Aldossary, Andreas Burger +9
Density functional theory (DFT) is the most widely used method for calculating molecular properties; however, its accuracy is often insufficient for quantitative predictions. Coupl…