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ORCIDKonstantinos Spiliopoulos
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2020 – today
- 2024
[i8]Hancong Pan, Xiaojing Zhu, Cantay Caliskan, Dino P. Christenson, Konstantinos Spiliopoulos, Dylan Walker, Eric D. Kolaczyk:
Stochastic gradient descent-based inference for dynamic network models with attractors. CoRR abs/2403.07124 (2024)- 2023
- [j23]Justin A. Sirignano, Jonathan F. MacArt, Konstantinos Spiliopoulos:
PDE-constrained models with neural network terms: Optimization and global convergence. J. Comput. Phys. 481: 112016 (2023) - [i7]Samuel Chun-Hei Lam
, Justin A. Sirignano, Konstantinos Spiliopoulos:
Kernel Limit of Recurrent Neural Networks Trained on Ergodic Data Sequences. CoRR abs/2308.14555 (2023) - 2022
- [j22]Justin A. Sirignano, Konstantinos Spiliopoulos:
Mean Field Analysis of Deep Neural Networks. Math. Oper. Res. 47(1): 120-152 (2022) - [j21]Benjamin J. Zhang, Youssef M. Marzouk, Konstantinos Spiliopoulos:
Geometry-informed irreversible perturbations for accelerated convergence of Langevin dynamics. Stat. Comput. 32(5): 78 (2022) - [j20]Samuel A. Isaacson, Jingwei Ma, Konstantinos Spiliopoulos:
Mean Field Limits of Particle-Based Stochastic Reaction-Diffusion Models. SIAM J. Math. Anal. 54(1): 453-511 (2022) - [i6]Jiahui Yu, Konstantinos Spiliopoulos:
Normalization effects on deep neural networks. CoRR abs/2209.01018 (2022) - 2021
- [j19]Solesne Bourguin, Siragan Gailus, Konstantinos Spiliopoulos:
Discrete-Time Inference for Slow-Fast Systems Driven by Fractional Brownian Motion. Multiscale Model. Simul. 19(3): 1333-1366 (2021) - [j18]Samuel A. Isaacson, Jingwei Ma, Konstantinos Spiliopoulos:
How Reaction-Diffusion PDEs Approximate the Large-Population Limit of Stochastic Particle Models. SIAM J. Appl. Math. 81(6): 2622-2657 (2021) - [i5]Justin A. Sirignano, Jonathan F. MacArt, Konstantinos Spiliopoulos:
PDE-constrained Models with Neural Network Terms: Optimization and Global Convergence. CoRR abs/2105.08633 (2021) - 2020
- [j17]Margaret Beck, Eric Cooper, Gabriel J. Lord, Konstantinos Spiliopoulos:
Selection of Quasi-stationary States in the Stochastically Forced Navier-Stokes Equation on the Torus. J. Nonlinear Sci. 30(4): 1677-1702 (2020) - [j16]Konstantinos Spiliopoulos:
Information Geometry for Approximate Bayesian Computation. SIAM/ASA J. Uncertain. Quantification 8(1): 229-260 (2020) - [j15]Konstantinos Spiliopoulos, Matthew R. Morse:
Importance Sampling for Slow-Fast Diffusions Based on Moderate Deviations. Multiscale Model. Simul. 18(1): 315-350 (2020) - [j14]Justin A. Sirignano, Konstantinos Spiliopoulos:
Mean Field Analysis of Neural Networks: A Law of Large Numbers. SIAM J. Appl. Math. 80(2): 725-752 (2020) - [i4]Jiahui Yu, Konstantinos Spiliopoulos:
Normalization effects on shallow neural networks and related asymptotic expansions. CoRR abs/2011.10487 (2020)
2010 – 2019
- 2019
- [i3]Justin A. Sirignano, Konstantinos Spiliopoulos:
Scaling Limit of Neural Networks with the Xavier Initialization and Convergence to a Global Minimum. CoRR abs/1907.04108 (2019) - [i2]Justin A. Sirignano, Konstantinos Spiliopoulos:
Asymptotics of Reinforcement Learning with Neural Networks. CoRR abs/1911.07304 (2019) - 2018
- [j13]Justin A. Sirignano, Konstantinos Spiliopoulos:
DGM: A deep learning algorithm for solving partial differential equations. J. Comput. Phys. 375: 1339-1364 (2018) - [j12]Siragan Gailus, Konstantinos Spiliopoulos:
Discrete-Time Statistical Inference for Multiscale Diffusions. Multiscale Model. Simul. 16(4): 1824-1858 (2018) - [j11]Jianfeng Lu, Konstantinos Spiliopoulos:
Analysis of Multiscale Integrators for Multiple Attractors and Irreversible Langevin Samplers. Multiscale Model. Simul. 16(4): 1859-1883 (2018) - 2017
- [j10]Matthew R. Morse, Konstantinos Spiliopoulos:
Moderate deviations for systems of slow-fast diffusions. Asymptot. Anal. 105(3-4): 97-135 (2017) - [j9]Andrew Papanicolaou, Konstantinos Spiliopoulos:
Dimension Reduction in Statistical Estimation of Partially Observed Multiscale Processes. SIAM/ASA J. Uncertain. Quantification 5(1): 1220-1247 (2017) - [j8]Justin A. Sirignano, Konstantinos Spiliopoulos:
Stochastic Gradient Descent in Continuous Time. SIAM J. Financial Math. 8(1): 933-961 (2017) - 2015
- [j7]Konstantinos Spiliopoulos:
Nonasymptotic performance analysis of importance sampling schemes for small noise diffusions. J. Appl. Probab. 52(3): 797-810 (2015) - [j6]Konstantinos Spiliopoulos:
Rare Event Simulation for Multiscale Diffusions in Random Environments. Multiscale Model. Simul. 13(4): 1290-1311 (2015) - [j5]Konstantinos Spiliopoulos, Richard B. Sowers:
Default Clustering in Large Pools: Large Deviations. SIAM J. Financial Math. 6(1): 86-116 (2015) - 2014
- [j4]Sergio Angel Almada, Konstantinos Spiliopoulos:
Scaling limits and exit law for multiscale diffusions. Asymptot. Anal. 87(1-2): 65-90 (2014) - [j3]Andrew Papanicolaou, Konstantinos Spiliopoulos:
Filtering the Maximum Likelihood for Multiscale Problems. Multiscale Model. Simul. 12(3): 1193-1229 (2014) - [c2]Paul Dupuis, Konstantinos Spiliopoulos:
Rare event simulation in the neighborhood of a rest point. WSC 2014: 564-573 - 2012
- [j2]Paul Dupuis, Konstantinos Spiliopoulos, Hui Wang:
Importance Sampling for Multiscale Diffusions. Multiscale Model. Simul. 10(1): 1-27 (2012) - 2011
- [c1]Paul Dupuis, Konstantinos Spiliopoulos, Hui Wang:
Rare event simulation for rough energy landscapes. WSC 2011: 504-515 - [i1]Paul Dupuis, Konstantinos Spiliopoulos, Hui Wang:
Importance Sampling for Multiscale Diffusions. CoRR abs/1107.5448 (2011)
2000 – 2009
- 2008
- [j1]Mark Freidlin, Konstantinos Spiliopoulos:
Reaction-diffusion equations with nonlinear boundary conditions in narrow domains. Asymptot. Anal. 59(3-4): 227-249 (2008)
Coauthor Index
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