DiffEqFlux.jl - A Julia Library for Neural Differential Equations

6 February 2019

Christopher Rackauckas

Papers citing "DiffEqFlux.jl - A Julia Library for Neural Differential Equations"

49 / 49 papers shown

Title
A comparative study of NeuralODE and Universal ODE approaches to solving Chandrasekhar White Dwarf equation Raymundo Vazquez Martinez Raj Abhijit Dandekar Rajat Dandekar Sreedath Panat 29 0 0 19 Oct 2024
Modeling chaotic Lorenz ODE System using Scientific Machine Learning Sameera S Kashyap Raj Abhijit Dandekar Rajat Dandekar Sreedath Panat AI4Cl AI4CE 29 0 0 09 Oct 2024
Graph Neural Ordinary Differential Equations for Coarse-Grained Socioeconomic Dynamics James Koch Pranab Roy Chowdhury Heng Wan Parin Bhaduri Jim Yoon Vivek Srikrishnan W. B. Daniel 24 0 0 25 Jul 2024
Gradients of Functions of Large Matrices Nicholas Krämer Pablo Moreno-Muñoz Hrittik Roy Søren Hauberg 40 0 0 27 May 2024
Physics-Informed Neural Networks for Satellite State Estimation J. Varey Jessica D. Ruprecht Michael Tierney Ryan Sullenberger 30 0 0 28 Mar 2024
A Deep Neural Network -- Mechanistic Hybrid Model to Predict Pharmacokinetics in Rat Florian Führer Andrea Gruber Holger Diedam A. Göller Stephan Menz S. Schneckener 28 3 0 13 Oct 2023
Effective Latent Differential Equation Models via Attention and Multiple Shooting German Abrevaya Mahta Ramezanian-Panahi Jean-Christophe Gagnon-Audet Pablo Polosecki Irina Rish S. Dawson Guillermo Cecchi G. Dumas MedIm 26 1 0 11 Jul 2023
Locally Regularized Neural Differential Equations: Some Black Boxes Were Meant to Remain Closed! Avik Pal Alan Edelman Chris Rackauckas 42 3 0 03 Mar 2023
Analyzing the Performance of Deep Encoder-Decoder Networks as Surrogates for a Diffusion Equation J. Q. Toledo-Marín J. Glazier Geoffrey C. Fox 35 4 0 07 Feb 2023
Eigen-informed NeuralODEs: Dealing with stability and convergence issues of NeuralODEs Tobias Thummerer Lars Mikelsons 19 3 0 07 Feb 2023
torchode: A Parallel ODE Solver for PyTorch Marten Lienen Stephan Günnemann LRM 24 11 0 22 Oct 2022
Neural ODEs as Feedback Policies for Nonlinear Optimal Control I. O. Sandoval Panagiotis Petsagkourakis Ehecatl Antonio del Rio Chanona 25 9 0 20 Oct 2022
Scientific Machine Learning for Modeling and Simulating Complex Fluids Kyle R. Lennon G. McKinley J. Swan AI4CE 17 27 0 10 Oct 2022
Homotopy-based training of NeuralODEs for accurate dynamics discovery Joon-Hyuk Ko Hankyul Koh Nojun Park W. Jhe 51 9 0 04 Oct 2022
NeuralFMU: Presenting a workflow for integrating hybrid NeuralODEs into real world applications Tobias Thummerer Johannes Stoljar Lars Mikelsons AI4CE 42 9 0 08 Sep 2022
Incremental Correction in Dynamic Systems Modelled with Neural Networks for Constraint Satisfaction Namhoon Cho Hyo-Sang Shin Antonios Tsourdos D. Amato 17 2 0 08 Sep 2022
Closed-Form Diffeomorphic Transformations for Time Series Alignment Iñigo Martinez E. Viles Igor García Olaizola AI4TS 17 7 0 16 Jun 2022
Automated differential equation solver based on the parametric approximation optimization A. Hvatov Tatiana Tikhonova 24 4 0 11 May 2022
Optimizing differential equations to fit data and predict outcomes S. Frank 33 4 0 16 Apr 2022
Neural Ordinary Differential Equations for Nonlinear System Identification Aowabin Rahman Ján Drgoňa Aaron Tuor J. Strube 27 22 0 28 Feb 2022
Deep learning and differential equations for modeling changes in individual-level latent dynamics between observation periods G. Köber R. Kalisch Lara Puhlmann A. Chmitorz Anita Schick Harald Binder 31 1 0 15 Feb 2022
An Overview of Healthcare Data Analytics With Applications to the COVID-19 Pandemic Z. Fei Y. Ryeznik O. Sverdlov C. Tan Weng Kee Wong 29 20 0 25 Nov 2021
A research framework for writing differentiable PDE discretizations in JAX A. Stanziola Simon Arridge B. Cox B. Treeby 32 8 0 09 Nov 2021
Multiple shooting for training neural differential equations on time series Evren Mert Turan J. Jäschke AI4TS 45 23 0 14 Sep 2021
NeuralFMU: Towards Structural Integration of FMUs into Neural Networks Tobias Thummerer Josef Kircher Lars Mikelsons AI4CE 23 8 0 09 Sep 2021
Parameter Inference with Bifurcation Diagrams Gregory Szép Neil Dalchau A. Csikász-Nagy 21 4 0 08 Jun 2021
Differentiable Multiple Shooting Layers Stefano Massaroli Michael Poli Sho Sonoda Taji Suzuki Jinkyoo Park Atsushi Yamashita Hajime Asama AI4CE 11 18 0 07 Jun 2021
Opening the Blackbox: Accelerating Neural Differential Equations by Regularizing Internal Solver Heuristics Avik Pal Yingbo Ma Viral B. Shah Chris Rackauckas 28 36 0 09 May 2021
Stiff Neural Ordinary Differential Equations Suyong Kim Weiqi Ji Sili Deng Yingbo Ma Chris Rackauckas AI4CE 27 144 0 29 Mar 2021
Deep learning approaches to surrogates for solving the diffusion equation for mechanistic real-world simulations J. Q. Toledo-Marín Geoffrey C. Fox J. Sluka J. Glazier MedIm AI4CE 21 8 0 10 Feb 2021
Control of Stochastic Quantum Dynamics by Differentiable Programming Frank Schafer P. Sekatski M. Koppenhöfer C. Bruder M. Kloc 18 17 0 04 Jan 2021
Neural Closure Models for Dynamical Systems Abhinav Gupta Pierre FJ Lermusiaux AI4CE 27 45 0 27 Dec 2020
Physics-Informed Machine Learning Simulator for Wildfire Propagation L. Bottero Francesco Calisto Giovanni Graziano Valerio Pagliarino Martina Scauda Sara Tiengo Simone Azeglio 22 7 0 12 Dec 2020
Deep dynamic modeling with just two time points: Can we still allow for individual trajectories? Maren Hackenberg Philipp Harms Michelle Pfaffenlehner Astrid Pechmann Janbernd Kirschner Thorsten Schmidt Harald Binder 11 4 0 01 Dec 2020
"Hey, that's not an ODE": Faster ODE Adjoints via Seminorms Patrick Kidger Ricky T. Q. Chen Terry Lyons 29 40 0 20 Sep 2020
TorchDyn: A Neural Differential Equations Library Michael Poli Stefano Massaroli Atsushi Yamashita Hajime Asama Jinkyoo Park AI4CE 22 24 0 20 Sep 2020
Augmenting Neural Differential Equations to Model Unknown Dynamical Systems with Incomplete State Information Robert Strauss 24 3 0 19 Aug 2020
Learning Differential Equations that are Easy to Solve Jacob Kelly J. Bettencourt Matthew J. Johnson David Duvenaud 38 111 0 09 Jul 2020
Accurate Characterization of Non-Uniformly Sampled Time Series using Stochastic Differential Equations S. Waele AI4TS 22 0 0 02 Jul 2020
A General Framework for Survival Analysis and Multi-State Modelling S. Groha Sebastian M. Schmon A. Gusev CML 22 8 0 08 Jun 2020
Predictive Coding Approximates Backprop along Arbitrary Computation Graphs Beren Millidge Alexander Tschantz Christopher L. Buckley 32 118 0 07 Jun 2020
Discretize-Optimize vs. Optimize-Discretize for Time-Series Regression and Continuous Normalizing Flows Derek Onken Lars Ruthotto BDL 32 52 0 27 May 2020
The JuliaConnectoR: a functionally oriented interface for integrating Julia in R S. Lenz Maren Hackenberg Harald Binder 16 8 0 13 May 2020
Julia Language in Machine Learning: Algorithms, Applications, and Open Issues Kaifeng Gao Gang Mei F. Piccialli S. Cuomo Jingzhi Tu Zenan Huo 23 55 0 23 Mar 2020
Approximation Capabilities of Neural ODEs and Invertible Residual Networks Han Zhang Xi Gao Jacob Unterman Tom Arodz 27 98 0 30 Jul 2019
A Differentiable Programming System to Bridge Machine Learning and Scientific Computing Mike Innes Alan Edelman Keno Fischer Chris Rackauckas Elliot Saba Viral B. Shah Will Tebbutt PINN 27 182 0 17 Jul 2019
Neural Jump Stochastic Differential Equations Junteng Jia Austin R. Benson BDL 22 222 0 24 May 2019
Neural Stochastic Differential Equations: Deep Latent Gaussian Models in the Diffusion Limit Belinda Tzen Maxim Raginsky DiffM 11 207 0 23 May 2019
ChronoMID - Cross-Modal Neural Networks for 3-D Temporal Medical Imaging Data Alexander Rakowski Petar Velickovic E. Dall’Ara Pietro Lio 16 2 0 12 Jan 2019