Inverse Problems

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20 papers in the last four weeks, up 186% on the four weeks before. 0.2% of all new papers.

Jul 13Week of Sep 28

Latest papers 161

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MonoPhysics: Estimating Geometry, Appearance, and Physical Parameters from Monocular Videos
May 28, 2026Daniel Rho, Jun Myeong Choi, Matthew Thornton +23D Reconstruction Monocular 3D Reconstruction
University of North Carolina at Chapel Hill · Meta
Battery-Sim-Agent: Leveraging LLM-Agent for Inverse Battery Parameter Estimation
May 28, 2026Jiawei Chen, Xiaofan Gui, Shikai Fang +4AI Agents for Scientific Discovery Large Language Model-Guided Optimization
Peking University Beijing, China · Microsoft Research Beijing, China · Chalmers University of Technology Gothenburg, Sweden
Trajectory Constraints for Imaging Inverse Problems
May 27, 2026Chaoyan Huang, Haijie Yuan, Saiprasad RavishankarImage Reconstruction Computational Imaging
Department of Computational Mathematics, Science, & Engineering, Michigan State University · Department of Electrical Engineering and Computer Science, University of Michigan · Department of Biomedical Engineering, Michigan State University
Stage-wise Distortion-Perception Traversal in Zero-shot Inverse Problems with Diffusion Models
May 27, 2026Jiawei Zhang, Ziyuan Liu, Leon Yan +2Bayesian Inverse Problems Diffusion-Based Inverse Problems
Department of Electronic Engineering, Tsinghua University, Beijing, China · Shenzhen International Graduate School, Tsinghua University, Shenzhen, China.
3D Magnetic Field Reconstruction and Mapping with Physics-Informed Neural Networks
May 25, 2026Haohan Yu, Zhanxu Hao, Bingzhi Li +3Physics-Informed ML Inverse Problems
State Key Laboratory of Dark Matter Physics, School of Physics and Astronomy, Shanghai Jiao Tong University, Shanghai, China · Key Laboratory for Particle Astrophysics and Cosmology (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China · Shanghai Key Laboratory for Particle Physics and Cosmology, Shanghai Jiao Tong University, Shanghai, China +1
Guided Flow Matching for Forward and Inverse PDE Problems with Sparse Observations: Algorithm and Theory
May 25, 2026Xifeng Zhang, Jin ZhaoFlow Matching PDE Solving
School of Mathematical Science Capital Normal University Beijing, 100048, China · Academy for Multidisciplinary Studies Capital Normal University2026 Beijing, 100048, China
A differentiable machine learning small-angle X-ray scattering analysis framework for structure elucidation of lipid nanoparticles
May 22, 2026Maria Bånkestad, Sandra Barman, Magnus Röding +11Parameter Identifiability Materials Science
RISE Research Institutes of Sweden, Division Digital Systems, Computer Science, Kista, Sweden · RISE Research Institutes of Sweden, Division Bioeconomy, Food Research and Innovation, Göteborg, Sweden · Sustainable Innovation & Transformational Excellence, Pharmaceutical Technology & Development, Operations, AstraZeneca Gothenburg, Mölndal, Sweden +5
Pointwise Metrics Mislead: An Evaluation Protocol for Multimodal Inverse Problems
May 21, 2026Mads H. Baattrup, Jörn Bach, Laurids Jeppe +4Bayesian Inverse Problems Multimodal Model Evaluation
Deutsches Elektronen-Synchrotron Hamburg, Germany · CERN Geneva, Switzerland · University of Hamburg Hamburg, Germany +1
Aerodynamic force reconstruction using physics-informed Gaussian processes
May 21, 2026Gledson Rodrigo Tondo, Igor Kavrakov, Guido MorgenthalPhysics-Informed ML Inverse Problems
Bauhaus-Universität Weimar Weimar, Germany · University of Cambridge Cambridge, United Kingdom
$\textit{BlockFormer}$ : Transformer-based inference from genomic contact maps
May 20, 2026Eloïse Touron, Pedro L. C. Rodrigues, Julyan Arbel +2Genomics Inverse Problems
Univ. Grenoble Alpes, Inria CNRS, Grenoble INP, LJK, France · TIMC, Univ. Grenoble Alpes CNRS, Grenoble INP, France
OpenSeisML: Open Large-Scale Real Seismic and well-log Dataset for Generative AI
May 19, 2026Ipsita Bhar, Huseyin Tuna Erdinc, Thales Souza +2Synthetic Data Generation Training Data Curation
Georgia Institute of Technology, Atlanta, USA · Osokey Ltd, Henley-on-Thames, UK
WaveGraphNet: Physics-Consistent Guided-Wave Damage Localization through Coupled Inverse-Forward Graph Learning
May 19, 2026Vinay Sharma, Aditya Bharade, Olga FinkGraph Neural Networks Inverse Problems
EPFL, Intelligent Maintenance and Operations Systems, Lausanne, Switzerland
Optimal Reconstruction from Linear Queries
May 19, 2026Yuval Filmus, Shay Moran, Elizaveta NesterovaQuery Complexity Inverse Problems
Technion – Israel Institute of Technology · Google Research
Diffusion Graph Posterior Sampling for Nonlinear Inverse Problems with Application to Electrical Impedance Tomography
May 19, 2026Giovanni S. Alberti, Damiana Lazzaro, Serena Morigi +2Image Reconstruction Diffusion-Based Inverse Problems
MaLGa Center, Department of Mathematics, University of Genova, Italy · Department of Mathematics, University of Bologna, Bologna, Italy · Department of Mathematics, Harbin Institute of Technology, China
MatPhys: Learning Material-Aware Physics Parameters for Deformable Object Simulation from Videos
May 19, 2026Yang Yang, Yiyan Wang, Zheming Liu +1Dynamic Scene Reconstruction Materials Property Prediction
1The University of Osaka · 3Huawei Technologies Japan K.K. · 2The University of Tokyo
Weighted Reverse Convolution for Feature Upsampling
May 17, 2026Wentong Li, Zhiyuan Qi, Zichen Zhao +2Vision Foundation Model Adaptation Inverse Problems
Nanjing University of Aeronautics and Astronautics · The Hong Kong Polytechnic University · Nanjing University
Radial-Component Predominant-Mode Inversion of Rayleigh Waves: Application to DAS-based Site Characterization
May 16, 2026Mrinal Bhaumik, Brady R. CoxDistributed Acoustic Sensing Inverse Problems
Department of Civil and Environmental Engineering, Utah State University, Logan, Utah, USA
Learning Normalized Energy Models for Linear Inverse Problems
May 15, 2026Nicolas Zilberstein, Santiago Segarra, Eero Simoncelli +1Bayesian Inverse Problems Energy-Based Models
Rice University, Houston, TX, USA · Flatiron Institute, New York, NY, USA · New York University, New York, NY, USA
Deciphering Neural Reparameterized Full-Waveform Inversion with Neural Sensitivity Kernel and Wave Tangent Kernel
May 14, 2026Ruihua Chen, Yisi Luo, Bangyu Wu +2Neural Tangent Kernel Inverse Problems
School of Mathematics and Statistics, Xi’an Jiaotong University, Xi’an, Shaanxi 710049, China · School of Mathematics and Statistics, Xi’an Jiaotong University, Xi’an, Shaanxi, China · School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu 610000, China
Neural Fields for NV-Center Inverse Sensing
May 13, 2026Zhixuan Zhao, Tao Zhong, Yixun Hu +2Implicit Neural Representations Inverse Problems
Princeton University · Tsinghua University
Twincher: Bijective Representation Learning for Robust Inversion of Continuous Systems
May 13, 2026Arkady GonoskovRepresentation Learning Invariant Representation Learning
Department of Physics, University of Gothenburg, SE-41296 Gothenburg, Sweden
On Hallucinations in Inverse Problems: Fundamental Limits and Provable Assessment Methods
May 13, 2026David Iagaru, Nina M. Gottschling, Anders C. Hansen +1Image Reconstruction Inverse Problems
CMAP, Ecole polytechnique, Institut Polytechnique de Paris, 91120 Palaiseau, France. · German Aerospace Center (DLR), Remote Sensing Technology Institute, Wessling, Germany. · Computing and Computational Sciences, Oak Ridge National Laboratory, Oak Ridge, Tennessee. +2
Stop Marginalizing My Dreams: Model Inversion via Laplace Kernel for Continual Learning
May 12, 2026Patryk Krukowski, Jacek Tabor, Przemysław Spurek +2Inverse Problems
Jagiellonian University · IDEAS Research Institute
Principled Design of Diffusion-based Optimizers for Inverse Problems
May 12, 2026Julio Oscanoa, Irmak Sivgin, Cagan Alkan +4Inference-Time Optimization Diffusion-Based Inverse Problems
Department of Bioengineering · Deparment of Electrical Engineering · Department of Radiology, Stanford University, USA.
Deep Probabilistic Unfolding for Quantized Compressive Sensing
May 12, 2026Gang Qu, Ping Wang, Siming Zheng +1Compressed Sensing Deep Unfolding
Westlake University, School of Engineering, Hangzhou, Zhejiang, China · Vivo Mobile Communication Co., Ltd., Hangzhou, Zhejiang, China.
A Stability Benchmark of Generative Regularizers for Inverse Problems
May 11, 2026Alexander Denker, Johannes Hertrich, Sebastian NeumayerGenerative Modeling Diffusion-Based Inverse Problems
Helmholtz Imaging, Deutsches Elektronen-Synchrotron DESY, Germany · ENS Paris & Inria, France · Chemnitz University of Technology, Germany
Total Generalized Variation regularization closes the gap between neural-eld and classical methods in seismic travel-time tomography
May 11, 2026Isao KurosawaSeismology PDE Inverse Problems
IVXA, Japan.
Outlier-Robust Diffusion Solvers for Inverse Problems
May 10, 2026Yang Zheng, Jiahua Liu, Tongyao Pang +2Diffusion Models for Image Restoration Robust Optimization
School of Computer Science and Engineering, University of Electronic Science and Technology of China · Yau Mathematical Sciences Center, Tsinghua University
The Direct Integration Theorem: A Rigorous Framework for Consistent Discrete Solutions of the Inverse Radon Problem
May 9, 2026Mikhail G. MozerovImage Reconstruction Computed Tomography
Institute for Information Transmission Problems, Russian Academy of Sciences, Moscow, 127051 Russia
FlowADMM: Plug-and-play ADMM with Flow-based Renoise-Denoise Priors
May 9, 2026Hendrik Sommerhoff, Michael MoellerAlternating Direction Method of Multipliers Image Restoration
Computer Vision Group, University of Siegen Hölderlinstraße 3, 57076 Siegen, Germany

May 28, 2026, cs.CVJ/K move · Enter open · S save

MonoPhysics: Estimating Geometry, Appearance, and Physical Parameters from Monocular Videos

Daniel Rho, Jun Myeong Choi, Matthew Thornton, Biswadip Dey+1

University of North Carolina at Chapel Hill · Meta

3D Reconstruction Monocular 3D Reconstruction Deformable Shape Reconstruction Inverse Problems Deformable Object Simulation

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Existing inverse physics methods recover physical parameters from multi-view videos, where geometric constraints across views resolve scale and 3D structure. In monocular settings, however, such constraints are absent, leading to severe scale ambiguity, inaccurate geometry, and weak coupling between appearance optimization and physical simulation. To address these challenges, we propose MonoPhysics, a framework for monocular inverse physics estimation of deformable objects that jointly optimizes geometry, appearance, and physical parameters using a differentiable simulator and 3D Gaussian Splatting. Our key contribution is removing the multi-view capture requirement of existing methods, a necessary step toward handling in-the-wild video. MonoPhysics introduces three visual-physical bridges: scene re-parameterization, physics-aware geometry refinement, and a differentiable position map. We evaluate on Vid2Sim, real-world captures, and a new dataset of elastic and plasticine objects that we introduce. MonoPhysics outperforms monocular baselines in future prediction and recovers Young's modulus on Vid2Sim with accuracy comparable to a multi-view baseline. Code and data are available at https://daniel03c1.github.io/MonoPhysics/.

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