LSY-Cython's Stars
computational-imaging/GraphPDE
camlab-ethz/ConvolutionalNeuralOperator
This repository is the official implementation of the paper Convolutional Neural Operators for robust and accurate learning of PDEs
lululxvi/deepxde
A library for scientific machine learning and physics-informed learning
hphong1990/PARCv2
Physics-aware recurrent convolutional neural network for spatiotemporal dynamics modeling
thuml/Time-Series-Library
A Library for Advanced Deep Time Series Models.
MPh-py/MPh
Pythonic scripting interface for Comsol Multiphysics
thuml/HelmFluid
About code release of "HelmFluid: Learning Helmholtz Dynamics for Interpretable Fluid Prediction", ICML 2024. https://arxiv.org/pdf/2310.10565
suan-chang/rain-UniCastX
BaratiLab/OFormer
thu-ml/DPOT
Code for "DPOT: Auto-Regressive Denoising Operator Transformer for Large-Scale PDE Pre-Training"
neuraloperator/CoDA-NO
Codomain attention neural operator for single to multi-physics PDE adaptation.
for-ai/parameter-efficient-moe
brandstetter-johannes/MP-Neural-PDE-Solvers
Repo to the paper "Message Passing Neural PDE Solvers"
BaratiLab/FactFormer
Official implementation of Scalable Transformer for PDE surrogate modelling
huggingface/peft
🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.
PolymathicAI/the_well
A 15TB Collection of Physics Simulation Datasets
nec-research/CAPE-ML4Sci
camlab-ethz/poseidon
Code for the paper "Poseidon: Efficient Foundation Models for PDEs"
delta-lab-ai/data_efficient_nopt
PolymathicAI/multiple_physics_pretraining
Code for paper "Multiple Physics Pretraining for Physical Surrogate Models
huggingface/transformers
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
kwuking/TimeMixer
[ICLR 2024] Official implementation of "TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting"
thuml/OpenLTM
Open Implementations of Large Time-Series Models
WooJin-Cho/Parameterized-Physics-informed-Neural-Networks
SalesforceAIResearch/gift-eval
LFhase/FeAT
[NeurIPS 2023] Understanding and Improving Feature Learning for Out-of-Distribution Generalization
DAMO-DI-ML/NeurIPS2023-One-Fits-All
The official code for "One Fits All: Power General Time Series Analysis by Pretrained LM (NeurIPS 2023 Spotlight)"
amazon-science/chronos-forecasting
Chronos: Pretrained Models for Probabilistic Time Series Forecasting
deepseek-ai/DeepSeek-R1
thuml/TimeXer
Official implementation for "TimeXer: Empowering Transformers for Time Series Forecasting with Exogenous Variables" (NeurIPS 2024)