Numerical Integration

16 papers with code • 0 benchmarks • 0 datasets

Numerical integration is the task to calculate the numerical value of a definite integral or the numerical solution of differential equations.


Latest papers with code

Efficient time stepping for numerical integration using reinforcement learning

lueckem/quadrature-ML 8 Apr 2021

To this end, adaptive schemes have been developed that rely on error estimators based on Taylor series expansions.

Meta-Learning Numerical Integration

08 Apr 2021

AutoInt: Automatic Integration for Fast Neural Volume Rendering

computational-imaging/automatic-integration 3 Dec 2020

For training, we instantiate the computational graph corresponding to the derivative of the network.

Neural Rendering Numerical Integration

03 Dec 2020

Hierarchical Deep Learning of Multiscale Differential Equation Time-Steppers

luckystarufo/multiscale_HiTS 22 Aug 2020

Our multiscale hierarchical time-stepping scheme provides important advantages over current time-stepping algorithms, including (i) circumventing numerical stiffness due to disparate time-scales, (ii) improved accuracy in comparison with leading neural-network architectures, (iii) efficiency in long-time simulation/forecasting due to explicit training of slow time-scale dynamics, and (iv) a flexible framework that is parallelizable and may be integrated with standard numerical time-stepping algorithms.

Numerical Integration

22 Aug 2020

Continuous-in-Depth Neural Networks

afqueiruga/ContinuousNet 5 Aug 2020

We first show that ResNets fail to be meaningful dynamical integrators in this richer sense.

Numerical Integration

05 Aug 2020

Bayesian Probabilistic Numerical Integration with Tree-Based Models

ImperialCollegeLondon/BART-Int NeurIPS 2020

The advantages and disadvantages of this new methodology are highlighted on a set of benchmark tests including the Genz functions, and on a Bayesian survey design problem.

Numerical Integration

09 Jun 2020

i-flow: High-dimensional Integration and Sampling with Normalizing Flows

i-flow/i-flow 15 Jan 2020

We introduce the code i-flow, a python package that performs high-dimensional numerical integration utilizing normalizing flows.

Numerical Integration

15 Jan 2020

On two ways to use determinantal point processes for Monte Carlo integration

guilgautier/DPPy NeurIPS 2019

In the absence of DPP machinery to derive an efficient sampler and analyze their estimator, the idea of Monte Carlo integration with DPPs was stored in the cellar of numerical integration.

Numerical Integration Point Processes

01 Dec 2019

Structured Variational Inference in Continuous Cox Process Models

VirgiAgl/STVB NeurIPS 2019

We propose a scalable framework for inference in an inhomogeneous Poisson process modeled by a continuous sigmoidal Cox process that assumes the corresponding intensity function is given by a Gaussian process (GP) prior transformed with a scaled logistic sigmoid function.

Numerical Integration Variational Inference

07 Jun 2019

AReS and MaRS - Adversarial and MMD-Minimizing Regression for SDEs

gabb7/AReS-MaRS 22 Feb 2019

Stochastic differential equations are an important modeling class in many disciplines.

Gaussian Processes Numerical Integration

22 Feb 2019