Niklas Linde

According to our database, Niklas Linde authored at least 11 papers between 2015 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Diffusion models for multivariate subsurface generation and efficient probabilistic inversion.

Roberto Miele, Niklas Linde

CoRR, July, 2025

An Energy-Based Model Approach to Rare Event Probability Estimation.

Lea Friedli, David Ginsbourger, Arnaud Doucet, Niklas Linde

SIAM/ASA J. Uncertain. Quantification, 2025

2024

Deep generative networks for multivariate fullstack seismic data inversion using inverse autoregressive flows.

Roberto Miele, Shiran Levy, Niklas Linde, Amilcar Soares, Leonardo Azevedo

Comput. Geosci., 2024

Conditioning of multiple-point statistics simulations to indirect geophysical data.

Shiran Levy, Lea Friedli, Grégoire Mariéthoz, Niklas Linde

Comput. Geosci., 2024

2023

Uncertainty Quantification and Experimental Design for Large-Scale Linear Inverse Problems under Gaussian Process Priors.

Cédric Travelletti, David Ginsbourger, Niklas Linde

SIAM/ASA J. Uncertain. Quantification, March, 2023

Variational Bayesian inference with complex geostatistical priors using inverse autoregressive flows.

Shiran Levy, Eric Laloy, Niklas Linde

Comput. Geosci., February, 2023

Efficient Bayesian travel-time tomography with geologically-complex priors using sensitivity-informed polynomial chaos expansion and deep generative networks.

Giovanni Angelo Meles, Macarena Amaya, Shiran Levy, Stefano Marelli, Niklas Linde

CoRR, 2023

2021

Fast ABC with Joint Generative Modelling and Subset Simulation.

Eliane Maalouf, David Ginsbourger, Niklas Linde

Proceedings of the Machine Learning, Optimization, and Data Science, 2021

2019

Gradient-based deterministic inversion of geophysical data with generative adversarial networks: Is it feasible?

Eric Laloy, Niklas Linde, Cyprien Ruffino, Romain Hérault, Gilles Gasso, Diederik Jacques

Comput. Geosci., 2019

2017

Efficient training-image based geostatistical simulation and inversion using a spatial generative adversarial neural network.

Eric Laloy, Romain Hérault, Diederik Jacques, Niklas Linde

CoRR, 2017

2015

Feature-preserving interpolation and filtering of environmental time series.

Grégoire Mariéthoz, Niklas Linde, Damien Jougnot, Hassan Rezaee

Environ. Model. Softw., 2015