220 skills found · Page 5 of 8
CarlosJose126 / NeuralODE ROMThis repository contains the files used in the paper " Reduced-order Model for Fluid Flows via Neural Ordinary Differential Equations"
jameslu01 / Neural PKNeural-ODE for Pharmacokinetics Modeling
zbliu98 / GRAM ODECode for the TMLR 2023 paper "GRAM-ODE: Graph-based Multi-ODE Neural Networks for Spatio-Temporal Traffic Forecasting"
aspuru-guzik-group / QNODEQuantum dynamics latent neural ode
SciML / OptimalControl.jlA component of the SciML scientific machine learning ecosystem for optimal control
BoyanJIANG / 4D Compositional RepresentationThis is an implementation of the CVPR'2021 paper "Learning Compositional Representation for 4D Captures with Neural ODE".
dataymeric / ClimODEPyTorch implementation of "ClimODE: Climate Forecasting With Physics-informed Neural ODEs"
IlyaOrson / Control NeuralODENeural ODEs as Feedback Policies for Nonlinear Optimal Control (IFAC 2023) https://doi.org/10.1016/j.ifacol.2023.10.1248
dgjung0220 / CLODEContinuous Exposure Learning for Low-light Image Enhancement using Neural ODEs, in ICLR 2025 (Spotlight)
simonmoesorensen / Neural Ode ProjectDeeplearning project at The Technological University of Denmark (DTU) about Neural ODEs for finding dynamics in ordinary differential equations and real world time series data
tksmatsubara / Symplectic Adjoint MethodCode for "Symplectic Adjoint Method for Exact Gradient of Neural ODE with Minimal Memory," NeurIPS, 2021.
SINTEF / Pseudo Hamiltonian Neural NetworksThe package phlearn for modelling pseudo-Hamiltonian systems by pseudo-Hamiltonian neural networks (PHNN), for ODEs and PDEs
tsinghua-fib-lab / Activity Simulation SANDThe official PyTorch implementation of "Learning to Simulate Daily Activities via Modeling Dynamic Human Needs" (WWW'23)
SDML-KU / QkvflowNeural ODE Transformers (ICLR 2025)
IdahoLabResearch / BIhNNsThe code enables to perform Bayesian inference in an efficient manner through the use of Hamiltonian Neural Networks (HNNs), Deep Neural Networks (DNNs), Neural ODEs, and Symplectic Neural Networks (SympNets) used with state-of-the-art sampling schemes like Hamiltonian Monte Carlo (HMC) and the No-U-Turn-Sampler (NUTS).
DAMO-DI-ML / WeatherODEThe official code for "Mitigating Time Discretization Challenges with WeatherODE: A Sandwich Physics-Driven Neural ODE for Weather Forecasting".
juliagusak / Neural Ode NormModels and code for the ICLR 2020 workshop paper "Towards Understanding Normalization in Neural ODEs"
alwaysbyx / Time Series Prediction Using Neural ODE And Neural FlowComparison for time series prediction using Neural-ODEs and Neural-Flows
frankschae / Control Of Stochastic Quantum Dynamics With Differentiable ProgrammingRepository for the Control of Stochastic Quantum Dynamics with Differentiable Programming paper.
GitTeaching / Predicting Using Neural ODEDeep Learning - Predicting using Neural Ordinary Differential Equations - torchdiffeq.
