Parameter Estimation

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9 papers in the last four weeks, against 2 the four weeks before. 0.1% of all new papers.

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Learning consistent molecular mechanics force fields from first principles
Oct 6, 2026Berkay Günes, Leif Seute, Jigyasa Nigam +1Parameter Estimation Molecular Dynamics Simulation
Max Planck Institute for Polymer Research Mainz, Germany · Heidelberg University, Germany · Heidelberg Institute for Theoretical Studies, Germany +1
Parameter Estimation in Machining Dynamics with Regenerative Delay and Nonsmooth Friction using Physics-Informed Neural Networks
Oct 5, 2026Meiyazhagan Jaganathan, Vikram Pakrashi, Aasifa RounakDynamical Systems Parameter Estimation
UCD Centre for Mechanics, Dynamical Systems and Risk Laboratory, School of Mechanical and Materials Engineering, University College Dublin, D04 V1W8, Dublin, Ireland
Learning Decision-Stump Thresholds in Context: Dynamics of Softmax Attention
Oct 5, 2026Hong Ha Le, Jackie Lok, Atsushi Nitanda +1Language Model Pretraining Softmax Attention
National University of Singapore · Princeton University · Nanyang Technological University
Inference for stochastic differential equations driven by weighted sub-fractional Brownian motion using neural networks and the Euler approximation
Sep 30, 2026J. H. Ramirez-GonzalezParameter Estimation Stochastic Differential Equations
Institute of Mathematics and Statistics, University of São Paulo (IME–USP), São Paulo, Brazil
On Parameters of Nonlinear Scalar Dynamics from Video: Invariants, Calibration, and Identifiability
Sep 30, 2026Wenjie Wang, Yuanyuan Wang, Zixiang Jiang +2Parameter Estimation Parameter Identifiability
University of Melbourne · Mohamed bin Zayed University of Artificial Intelligence · Carnegie Mellon University
Hybrid Joint-Selective Optimization: Reduced-Space Levenberg-Marquardt Refinement of Low-Dimensional Parameters of Interest
Sep 29, 2026Muhammad Luthfi Shahab, Gabriella Alfa Indahsari, Imam Mukhlash +1Parameter Estimation Second-Order Optimization
Department of Mathematics, Institut Teknologi Sepuluh Nopember, Surabaya, 60111, Indonesia · Department of Mathematics, Khalifa University of Science & Technology, Abu Dhabi, PO Box 127788, United Arab Emirates
Simulation-Based Inference for Plate Reverb System Identification
Sep 28, 2026Dylan Sechet, Marc Evrard, Matthieu KowalskiParameter Estimation Bayesian Inverse Problems
Laboratoire Interdisciplinaire des Sciences du Numérique Université Paris-Saclay, Inria, CNRS, CentraleSupélec
Uncertainty Quantification in Cardiac Model Personalisation from Ultrafast Ultrasound
Sep 28, 2026Camilla Ferrario, Maelys Venet, Olivier Villemain +1Parameter Estimation Uncertainty Quantification
CHU Bordeaux · EPIONE
Error Bounds for Statistical Estimators in BTL Model with Parametric Multivariate Utility Functions
Sep 22, 2026Yicheng Li, Huifu XuParameter Estimation Minimax Estimation
Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong.
Statistical Gains from Looped Estimation under Parameter Budgets
Sep 22, 2026Xinyu Tian, Xiaotong ShenParameter Estimation Minimax Estimation
School of Statistics, University of Minnesota
One Intervention per Component is Enough: Towards Identifiability in Linear Stochastic Dynamics from Steady State
Sep 17, 2026Saber SalehkaleybarParameter Estimation Stochastic Differential Equations
Leiden Institute of Advanced Computer Science, Leiden University, The Netherlands
Generalised Score Matching on Convex Domains
Sep 10, 2026Nishanth Shetty, Saisuchith Mahajan, Chandra Sekhar SeelamantulaScore Matching Parameter Estimation
Department of Electrical Engineering Indian Institute of Science, Bengaluru 560012
DeSyR: A Decoupled Symbolic Recovery Framework with PINN-Guided Structure Search and Physics-Informed Coefficient Refinement
Sep 1, 2026Pancheng Niu, Jun Guo, Qiaolin He +2Parameter Estimation Physics-Informed ML
Chengdu University of Information Technology, College of Applied Mathematics, Chengdu, 610225, China · Sichuan University, School of Mathematics, Chengdu, 610065, China · Hong Kong Polytechnic University, Department of Computing, Hong Kong, 999077, China +1
Variational Parameter Calibration with Physics-Aware Latent-Space Surrogates
Aug 11, 2026Qiyao Zhou, Xujia Zhu, Pierre Joli +2Neural Surrogate Modeling Parameter Estimation
LMEE, UnivEvry, Université Paris-Saclay, Evry, France · L2S, Université Paris-Saclay, CNRS, CentraleSupéléc, Gif-sur-Yvette, France · CEREA, ENPC, EDF R&D, Institut Polytechnique de Paris, Île-de-France, France
Scalable estimation of VARMA models
Aug 6, 2026Daniel Paulin, Victor ElviraMultivariate Time Series Forecasting Parameter Estimation
College of Computing & Data Science Nanyang Technological University Singapore · School of Mathematics University of Edinburgh Edinburgh, UK
Wrong Operator or Blind Design? A Reference-Free Diagnostic for Physics-Informed Coefficient Learning
Aug 4, 2026Eric FockParameter Estimation Parameter Identifiability
PIMENT Laboratory, Universit´e de La R´eunion, Le Tampon 97430, La R´eunion, France
Band-Count Dense Modal Estimation with Fixed-Frequency Differentiable Resonator Refinement
Aug 1, 2026Minhui Lu, Joshua D. ReissParameter Estimation
Centre for Digital Music Queen Mary University of London London, United Kingdom
Simulation-Based Plate-Reverb Parameter Estimation from a Single Impulse Response
Aug 1, 2026Minhui Lu, Joshua D. ReissParameter Estimation
Centre for Digital Music Queen Mary University of London London, United Kingdom
Simulation-based parameter estimation via a combination of embedded normalizing flows and implied empirical probabilities under moment restrictions
Jul 27, 2026Getachew K. BefekaduSimulation-Based Inference Parameter Estimation
DEPARTMENT OF ELECTRICAL & COMPUTER ENGINEERING, COLLEGE OF ENGINEERING, PHYSICS, AND COMPUTING, THE CATHOLIC UNIVERSITY OF AMERICA, WASHINGTON, DC 20064, USA.
Simulation-Based Empirical Bayes
Jul 23, 2026Xinwei Shen, Diana Cai, Cheng Zhang +1Simulation-Based Inference Parameter Estimation
Department of Statistics University of Washington · Department of Computer Science Cornell University · School of Mathematical Sciences and Center for Statistical Science Peking University +1
An Introduction to Bayesian and Frequentist Simulation-Based Inference with Machine Learning
Jul 23, 2026Maximilian Dax, Theo Heimel, Gilles LouppeSimulation-Based Inference Parameter Estimation
ELLIS Institute Tübingen, Max Planck Institute for Intelligent Systems, Tübingen AI Center, Tübingen, Germany · CP3, Université catholique de Louvain, Louvain-la-Neuve, Belgium · Montefiore Institute, University of Liège, Belgium
Black-Box Optimization for Identifying and Inverting Audio Dynamic Range Control Effects
Jul 22, 2026Haoran Sun, Dominique Fourer, Hichem MaarefParameter Estimation
IBISC (EA 4526), Univ. Évry Paris-Saclay
Program Synthesis for Simulation-Based Inference: Joint Model Selection and Parameter Estimation
Jul 20, 2026Siddharth Mishra-SharmaSimulation-Based Inference Parameter Estimation
Faculty of Computing & Data Sciences Boston University · Boston University
Agentic Calibration of Grey-Box Simulation Models: An LLM-Driven Alternative
Jul 17, 2026David Gómez-Guillén, Mireia Diaz, Josep Lluis Arcos +1Parameter Estimation Black-Box Optimization
Unit of Infections and Cancer – Information and Interventions (UNIC-I&I), Cancer Epidemiology Research Program, Catalan Institute of Oncology-IDIBELL, L’Hospitalet de Llobregat, Spain · Autonomous University of Barcelona (UAB), Spain · Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Ministerio de Ciencia, Innovación y Universidades, Madrid, Spain +1
RTS Smoother-Guided Learning of Physics-Based Neural Differential Models
Jul 16, 2026Ahmet Demirkaya, Georgios Stratis, Tales Imbiriba +2Dynamical Systems Parameter Estimation
Department of Electrical and Computer Engineering Northeastern University · Department of Computer Science University of Massachusetts Boston · Emory University
Physically Consistent Parameter Inference: Transparent Machine Learning Emulation in High Energy Physics and Cosmology
Jul 14, 2026Jorge Alda, Jacobo Asorey, Alejandro Mir +1Parameter Estimation High-Energy Physics
Dipartimento di Fisica e Astronomia “Galileo Galilei”, Universit`a degli Studi di Padova & INFN Sezione di Padova, via Marzolo 8, 35131 Padova, Italy · Centro de Astropart´ıculas y F´ısica de Altas Energ´ıas (CAPA), Pedro Cerbuna 12 50009 Zaragoza, Spain · Departamento de F´ısica Te´orica, Facultad de Ciencias, Universidad de Zaragoza, Pedro Cerbuna 12, E-50009 Zaragoza, Spain
NeuroMem-FHP: A Likelihood-Free Deep Learning Framework for Parameter Estimation of Fractional Hawkes Process
Jul 13, 2026Neha Gupta, Aditya MaheshwariTemporal Point Processes Parameter Estimation
Operations Management and Quantitative Techniques Area, Indian Institute of Management Indore, Indore 453556, India.
Representation Learning for Semiparametric Causal Mediation Analysis under No Essential Heterogeneity
Jul 12, 2026Roberto Faleh, Sofia Morelli, Holger BrandtSemiparametric Inference Parameter Estimation
Methods Center University of Tübingen, Germany
Sensitivity to Subjective Expected Utility Maximization: A Methodological Study, with an Illustrative Application to LLM Decision-Making
Jul 8, 2026Jeff HelznerParameter Estimation Parameter Identifiability
The Regularization Parameter: Sparse Precision Matrix Estimation
Jul 7, 2026Aryan Eftekhari, Daniel Sergio Vega, Ernst-Jan Camiel Wit +1Graph Structure Learning Parameter Estimation
Institute of Computing, Faculty of Informatics, Universit`a della Svizzera italiana (USI), Lugano, Switzerland

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Learning consistent molecular mechanics force fields from first principles

Berkay Günes, Leif Seute, Jigyasa Nigam, Frauke Gräter

Max Planck Institute for Polymer Research Mainz, Germany · Heidelberg University, Germany · Heidelberg Institute for Theoretical Studies, Germany+1

Parameter Estimation Molecular Dynamics Simulation

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Classical force fields (FFs) remain the workhorse for large-scale simulations even as machine-learned interatomic potentials (MLIPs) approach ab initio accuracy. They decompose total configuration energies into simple effective interactions whose parameters are traditionally assigned based on atom or bond types, enabling efficient simulations but also limiting their ability to adapt across configurations. Recent machine learning approaches have improved the accuracy and transferability of bonded parameters in these FFs by inferring them as functions of local atomic environments, but still rely on empirical nonbonded parameters for practical simulations. In this work, we introduce a unified approach, \texttt{grappa-fullFF}, which learns both bonded and nonbonded parameters \emph{consistently} and simultaneously from ab initio reference data. By incorporating physically inspired regularization via supervision of the electrostatic potential and an architecture that facilitates charge equilibration, our model recovers accurate electric response properties, achieves state-of-the-art accuracy on geometry optimization benchmarks, and reproduces the conformational sampling of both classical and existing machine-learned FFs, without relying on externally assigned nonbonded parameters.

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