Stars
Implementation of the Aurora model for Earth system forecasting
A comprehesive survey about foundation models for weather and cliamte data understanding.
AI for Science 论文解读合集（持续更新ing），论文/数据集/教程下载：hyper.ai
[NeurIPS '24] Code repo for the paper entitled "Learning Structured Representations with Hyperbolic Embeddings" at NeurIPS 2024
PyTorch implementation of the NIPS-17 paper "Poincaré Embeddings for Learning Hierarchical Representations"
Simple PyTorch Implementation of Physics Informed Neural Network (PINN)
PINNs-Torch, Physics-informed Neural Networks (PINNs) implemented in PyTorch.
Open-source C++ code for Shake-the-box, particle tracking algorithm
A differentiable PDE solving framework for machine learning
Official PyTorch implementation of Hyperbolic Neural Networks++
Official PyTorch implementation of the ICML 2024 paper "Hyperbolic Active Learning for Semantic Segmentation under Domain Shift"
Physics-informed deep super-resolution of spatiotemporal data
Training and evaluating NBM and SPAM for interpretable machine learning.
ABIDE Preprocessed Initiative
Model interpretability and understanding for PyTorch
Riemannian Adaptive Optimization Methods with pytorch optim
Code for the paper Learning the Predictability of the Future (CVPR 2021)
A 15TB Collection of Physics Simulation Datasets
A data-driven method combining symbolic regression and compressed sensing for accurate & interpretable models.
Implementations of recent research prototypes/demonstrations using MONAI.
The code for the paper "[ICLR'24]MG-TSD: Multi-Granularity Time Series Diffusion Models with Guided Learning Process"
[CVPR 2024 Highlight] Logit Standardization in Knowledge Distillation
PyTorch implementation of the diffusion-based method for CFD data super-resolution proposed in the paper "A Physics-informed Diffusion Model for High-fidelity Flow Field Reconstruction".
[ICCV'23] Official PyTorch implementation for paper "Exploring Predicate Visual Context in Detecting Human-Object Interactions"