1. The Gaussian Latent Machine: Efficient Prior and Posterior Sampling for Inverse Problems
   2025/05/19 by Muhamed Kuric, Martin Zach, Kuric, Muhamed +7 · 3 citations
   Computer Science · Mathematics · #65C05 #65C40 #65C60 #68U10 #Bayesian Methods and Mixture Models #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #FOS: Electrical engineering #Gaussian Processes and Bayesian Inference #Image and Video Processing (eess.IV) #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Markov Chains and Monte Carlo Methods #electronic engineering #information engineering
2. Efficient Bayesian Computation Using Plug-and-Play Priors for Poisson Inverse Problems
   2025/03/20 by Klatzer, Teresa, Melidonis, Savvas, Pereyra, Marcelo +1 · 3 citations
   #53B21 #60H35 #62F15 #65C40 #65C60 #65J22 #68U10 #Computation (stat.CO) #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (stat.ML) #Numerical Analysis (math.NA)
3. Diffusion at Absolute Zero: Langevin Sampling Using Successive Moreau Envelopes [conference paper]
   2025/02/03 by Habring, Andreas, Falk, Alexander, Pock, Thomas · 3 citations
   #65C05 #65C40 #65C60 #68U10 #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #FOS: Mathematics #G.1.6 #G.3 #Numerical Analysis (math.NA) #Optimization and Control (math.OC)
4. Bayesian D-Optimal Experimental Designs via Column Subset Selection
   2024/02/25 by Eswar, Srinivas, Rao, Vishwas, Saibaba, Arvind K. · 1 citation
   #35R30 #62F15 #62K05 #65C60 #68W20 #FOS: Mathematics #Numerical Analysis (math.NA)
5. Ensemble-Based Annealed Importance Sampling
   2024/01/28 by Chen, Haoxuan, Ying, Lexing · 1 citation
   #62P35 #65C05 #65C40 #65C60 #Computation (stat.CO) #Computational Physics (physics.comp-ph) #FOS: Computer and information sciences #FOS: Mathematics #FOS: Physical sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Numerical Analysis (math.NA)
6. Accurate, scalable, and efficient Bayesian optimal experimental design with derivative-informed neural operators
   2023/12/22 by Go, Jinwoo, Chen, Peng · 1 citation
   #35Q62 #35Q93 #35R30 #62F15 #62K05 #65C60 #90C27 #Computational Engineering #FOS: Computer and information sciences #FOS: Mathematics #Finance #G.1.8 #I.5.2 #I.6.4 #Methodology (stat.ME) #Optimization and Control (math.OC) #and Science (cs.CE)
7. Subgradient Langevin Methods for Sampling from Non-smooth Potentials
   2023/08/02 by Andreas Habring, Habring, Andreas, Martin Höller +3 · 4 citations
   Engineering · Mathematics · Physics and Astronomy · #65C05 #65C40 #65C60 #68U10 #Computation (stat.CO) #FOS: Computer and information sciences #FOS: Mathematics #G.1.6 #G.3 #Markov Chains and Monte Carlo Methods #NMR spectroscopy and applications #Optimization and Control (math.OC) #Sparse and Compressive Sensing Techniques
8. Generative adversarial networks with physical sound field priors
   2023/08/01 by Karakonstantis, Xenofon, Fernandez-Grande, Efren · 2 citations
   #65C60 #Artificial Intelligence (cs.AI) #Audio and Speech Processing (eess.AS) #FOS: Computer and information sciences #FOS: Electrical engineering #I.2.10 #I.5.4 #J.2.3 #electronic engineering #information engineering
9. Robust A-Optimal Experimental Design for Bayesian Inverse Problems
   2023/05/05 by Attia, Ahmed, Leyffer, Sven, Munson, Todd · 1 citation
   #35Q62 #35Q93 #35R30 #62F15 #62K05 #65C60 #93E35 #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Optimization and Control (math.OC)
10. Posterior-Variance-Based Error Quantification for Inverse Problems in Imaging
    2022/12/23 by Narnhofer, Dominik, Habring, Andreas, Holler, Martin +1 · 3 citations
    #62F15 #65C40 #65C60 #65J22 #68U10 #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #FOS: Mathematics #Probability (math.PR)
11. Unbalanced Kantorovich-Rubinstein distance, plan, and barycenter on finite spaces: A statistical perspective
    2022/11/16 by Florian Heinemann, Hundrieser, Shayan, Heinemann, Florian +5 · 1 citation
    Mathematics · #05C05 #62D99 #62G09 #62R20 #65C60 #90C08 #Advanced Statistical Methods and Models #FOS: Computer and information sciences #Methodology (stat.ME)
12. Optimal design of large-scale nonlinear Bayesian inverse problems under model uncertainty
    2022/11/08 by Alen Alexanderian, Alexanderian, Alen, Ruanui Nicholson +3 · 2 citations
    Computer Science · Decision Sciences · #35R30 #62F15 #62K05 #65C60 #Advanced Multi-Objective Optimization Algorithms #Computation (stat.CO) #FOS: Computer and information sciences #FOS: Mathematics #Gaussian Processes and Bayesian Inference #Numerical Analysis (math.NA) #Probabilistic and Robust Engineering Design
13. Adaptive importance sampling based on fault tree analysis for piecewise deterministic Markov process
    2022/09/17 by Guillaume Chennetier, Hassane Chraibi, Chennetier, Guillaume +5 · 1 voice · 1 citation
    Mathematics · #60J25 #62L12 #65C05 #65C60 #Applications (stat.AP) #Computation (stat.CO) #FOS: Computer and information sciences #FOS: Mathematics #Probability (math.PR) #math.PR #stat.AP #stat.CO
14. Exact and approximate computation of the scatter halfspace depth
    2022/08/10 by Xiaohui Liu, Liu, Xiaohui, Yuzi Liu +7 · 1 citation
    Decision Sciences · Mathematics · #62G35 #62H12 #65C60 #Advanced Statistical Methods and Models #Computation (stat.CO) #FOS: Computer and information sciences #Optimal Experimental Design Methods #Statistical Methods and Inference
15. Efficient Bayesian computation for low-photon imaging problems
    2022/06/10 by Melidonis, Savvas, Dobson, Paul, Altmann, Yoann +2 · 3 citations
    #62E17 #62F30 #62H10 #65C40 #65C60 #65J22 #68U10 (Primary) 62F15 #68W25 (Secondary) #Computation (stat.CO) #FOS: Computer and information sciences
16. On resampling schemes for particle filters with weakly informative\n observations
    2022/03/18 by ChopinNicolas, Sumeetpal S. Singh, Chopin, Nicolas +5 · 2 citations
    Computer Science · Environmental Science · Mathematics · #60J25 #65C60 #Computation (stat.CO) #FOS: Computer and information sciences #FOS: Mathematics #Hydrology and Drought Analysis #Methodology (stat.ME) #Primary 65C35 #Probability (math.PR) #Statistical Methods and Bayesian Inference #Target Tracking and Data Fusion in Sensor Networks #secondary 65C05
17. Dependence model assessment and selection with DecoupleNets
    2022/02/07 by Marius Hofert, Avinash Prasad, Hofert, Marius +3 · 1 citation
    Chemistry · Computer Science · #00A72 #60E05 #62H99 #62M10 #62M45 #65C10 #65C60 #Applications (stat.AP) #Computation (stat.CO) #Computational Finance (q-fin.CP) #FOS: Computer and information sciences #FOS: Economics and business #Image and Signal Denoising Methods #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Neural Networks and Applications #Risk Management (q-fin.RM) #Spectroscopy and Chemometric Analyses
18. Pairwise interaction function estimation of Gibbs point processes using basis expansion
    2021/10/11 by Ba, Ismaïla, Coeurjolly, Jean-François, Cuevas-Pacheco, Francisco · 2 citations
    #60G55 (Primary) 62J07 #62H11 #65C60 #97K80 (Secondary) #FOS: Mathematics #G.3 #Statistics Theory (math.ST)
19. Novel Deep neural networks for solving Bayesian statistical inverse
    2021/02/08 by Antil, Harbir, Elman, Howard C, Onwunta, Akwum +1 · 1 citation
    #65C40 #65C60 #65F22 #65N12 #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Numerical Analysis (math.NA) #Optimization and Control (math.OC)
20. Context-aware surrogate modeling for balancing approximation and sampling costs in multi-fidelity importance sampling and Bayesian inverse problems
    2020/10/22 by Alsup, Terrence, Peherstorfer, Benjamin · 1 citation
    #35R60 #62F15 #65C05 #65C60 #FOS: Computer and information sciences #FOS: Mathematics #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Numerical Analysis (math.NA)
21. Multivariate time-series modeling with generative neural networks
    2020/02/25 by Marius Hofert, Hofert, Marius, Avinash Prasad +3 · 1 citation
    Decision Sciences · Economics, Econometrics and Finance · #00A72 #60E05 #62H99 #62M10 #65C10 #65C60 #Complex Systems and Time Series Analysis #FOS: Computer and information sciences #Financial Risk and Volatility Modeling #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Methodology (stat.ME) #Stock Market Forecasting Methods
22. Rank Bounds for Approximating Gaussian Densities in the Tensor-Train Format
    2020/01/22 by Paul Rohrbach, Sergey Dolgov, Rohrbach, Paul B. +5 · 2 citations
    Computer Science · Engineering · Mathematics · #15A23 #15A69 #41A10 #65C60 #65D15 #65D32 #FOS: Mathematics #Numerical Analysis (math.NA) #Solar Radiation and Photovoltaics #Sparse and Compressive Sensing Techniques #Statistics Theory (math.ST) #Tensor decomposition and applications
23. Stable and Robust LQR Design via Scenario Approach
    2020/01/16 by Scampicchio, Anna, Aravkin, Aleksandr, Pillonetto, Gianluigi · 2 citations
    #65C60 #65K10 #90C30 #FOS: Mathematics #Optimization and Control (math.OC)
24. IRLS for Sparse Recovery Revisited: Examples of Failure and a Remedy
    2019/10/15 by Aleksandr Y. Aravkin, James V. Burke, Aravkin, Aleksandr Y. +3 · 1 citation
    Earth and Planetary Sciences · Engineering · #60G35 #65C60 #80M50 #Electrical and Bioimpedance Tomography #FOS: Mathematics #Optimization and Control (math.OC) #Seismic Imaging and Inversion Techniques #Sparse and Compressive Sensing Techniques #Statistics Theory (math.ST)
25. Fitting a manifold of large reach to noisy data
    2019/10/11 by Fefferman, Charles, Ivanov, Sergei, Lassas, Matti +1 · 2 citations
    #65C60 #FOS: Mathematics #Statistics Theory (math.ST)
26. Randomization and reweighted \ℓ₁-minimization for A-optimal design\n of linear inverse problems
    2019/06/10 by Elizabeth Herman, Alen Alexanderian, Herman, Elizabeth +3 · 1 citation
    Computer Science · Decision Sciences · #35Q62 #35R30 #62F15 #62K05 #65C60 #68W20 #Advanced Multi-Objective Optimization Algorithms #Computation (stat.CO) #FOS: Computer and information sciences #FOS: Mathematics #Gaussian Processes and Bayesian Inference #Numerical Analysis (math.NA) #Probabilistic and Robust Engineering Design
27. A Latent Variational Framework for Stochastic Optimization
    2019/05/05 by Casgrain, Philippe · 1 citation
    #49 #60 #65C30 #65C60 #Computation (stat.CO) #FOS: Computer and information sciences #FOS: Mathematics #G.1.6 #G.3 #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Probability (math.PR)
28. Quasi-random sampling for multivariate distributions via generative neural networks
    2018/11/01 by Marius Hofert, Avinash Prasad, Hofert, Marius +3 · 2 citations
    Computer Science · Decision Sciences · Mathematics · #00A72 #60E05 #62H99 #65C10 #65C60 #Bayesian Methods and Mixture Models #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Mathematical Approximation and Integration #Probabilistic and Robust Engineering Design
29. Statistical Treatment of Inverse Problems Constrained by Differential Equations-Based Models with Stochastic Terms
    2018/10/15 by Constantinescu, Emil M., Petra, Noemi, Bessac, Julie +1 · 1 citation
    #35Q62 #35Q93 #35R30 #62F15 #62H10 #62M20 #65C60 #65K10 #FOS: Computer and information sciences #FOS: Mathematics #Methodology (stat.ME) #Optimization and Control (math.OC)
30. Approximation and sampling of multivariate probability distributions in\n the tensor train decomposition
    2018/10/02 by Sergey Dolgov, Dolgov, Sergey, Karim Anaya‐Izquierdo +5 · 5 citations
    Decision Sciences · Mathematics · #15A23 #15A69 #62F15 #65C05 #65C40 #65C60 #65D15 #65D32 #FOS: Mathematics #Mathematical Approximation and Integration #Numerical Analysis (math.NA) #Probabilistic and Robust Engineering Design #Probability (math.PR) #Statistics Theory (math.ST) #Tensor decomposition and applications

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