Alternatives and similar repositories for Predicting-using-Neural-ODE

Users that are interested in Predicting-using-Neural-ODE are comparing it to the libraries listed below

• DiffEqML / kairos
  Model hub for all your DiffeqML needs. Pretrained weights, modules, and basic inference infrastructure
  ☆28Updated 2 years ago
• jaggbow / magnet
  This repository contains code for the paper "MAgNet: Mesh-Agnostic Neural PDE Solver" https://arxiv.org/abs/2210.05495
  ☆38Updated 2 years ago
• PredictiveIntelligenceLab / LOCA
  ☆15Updated 2 years ago
• stathius / wave_propagation
  Predicting wave propagation on shallow water with deep neural networks
  ☆22Updated 2 years ago
• Rose-STL-Lab / AutoODE-DSL
  ☆13Updated 4 years ago
• delta-lab-ai / pde-controller
  ☆25Updated 6 months ago
• thuml / RoPINN
  About Code release for “RoPINN: Region Optimized Physics-Informed Neural Networks” (NeurIPS 2024), https://arxiv.org/abs/2405.14369
  ☆59Updated 5 months ago
• CognitiveModeling / finn
  The public repository about our joint FINN research project
  ☆37Updated 3 years ago
• isds-neu / PiSL
  A python implementation of Physics-informed Spline Learning for nonlinear dynamics discovery.
  ☆27Updated 4 years ago
• bw-park / ACSSM
  Pytorch Implmentation of Amortized Control of Continuous State Space Feynman-Kac Model for Irregular Time Series (ACSSM), ICLR 2025 Oral
  ☆21Updated 9 months ago
• simonmoesorensen / neural-ode-project
  Deeplearning project at The Technological University of Denmark (DTU) about Neural ODEs for finding dynamics in ordinary differential equ…
  ☆17Updated 3 years ago
• holl- / PDE-Control
  Code for the ICLR 2020 paper "Learning to Control PDEs"
  ☆35Updated 5 years ago
• Rose-STL-Lab / Equivariant-Net
  ☆35Updated 2 years ago
• ASK-Berkeley / physics-NNs-hard-constraints
  [ICLR 2024] Scaling physics-informed hard constraints with mixture-of-experts.
  ☆36Updated last year
• AI4Science-WestlakeU / le-pde-uq
  [AAAI24] LE-PDE-UQ endows deep learning-based surrogate models with robust and efficient uncertainty quantification capabilities for both…
  ☆16Updated last year
• jayroxis / qres
  Learning with Higher Expressive Power than Neural Networks (On Learning PDEs)
  ☆16Updated 4 years ago
• HwijaeSon / AL-PINNs
  Official code for AL-PINNS: Augmented Lagrangian relaxation method for Physics-Informed Neural Networks
  ☆12Updated 2 years ago
• networkslab / rnn_flow
  ☆23Updated 4 years ago
• PhIMaL / temporal_normalizing_flows
  ☆11Updated 4 years ago
• yuan-yin / CoDA
  Generalizing to New Physical Systems via Context-Informed Dynamics Model
  ☆25Updated last year
• USC-Melady / ICLR2020-PADGN
  Official PyTorch implementation of "Physics-aware Difference Graph Networks for Sparsely-Observed Dynamics" (https://openreview.net/forum…
  ☆52Updated 5 years ago
• alwaysbyx / Time-series-prediction-using-Neural-ODE-and-Neural-Flow
  Comparison for time series prediction using Neural-ODEs and Neural-Flows
  ☆16Updated 3 years ago
• yuan-yin / LEADS
  Learning Dynamical Systems that Generalize Across Environments
  ☆20Updated 3 years ago
• crispitagorico / torchspde
  Neural Stochastic PDEs: resolution-invariant modelling of continuous spatiotemporal dynamics
  ☆53Updated 3 years ago
• luckystarufo / MrCAE
  a multiresolution convolutional autoencoder architecture
  ☆23Updated 4 years ago
• AlexTMallen / koopman-forecasting
  Long-term probabilistic forecasting of quasiperiodic phenomena using Koopman theory
  ☆36Updated 3 years ago
• snap-stanford / lamp
  [ICLR23] First deep learning-based surrogate model that jointly learns the evolution model and optimizes computational cost via remeshing
  ☆42Updated last year
• dbgannon / NNets-and-Diffeqns
  jupyter notebooks for the neural nets and differential equation paper
  ☆28Updated 4 years ago
• sungyongs / dpgn
  Differentiable Physics-informed Graph Networks
  ☆67Updated 5 years ago
• SmartTURB / diffusion-lagr
  Synthetic Lagrangian Turbulence by Generative Diffusion Models
  ☆26Updated last year