wanghonghui1998

wanghonghui1998's Stars

• vsitzmann/awesome-implicit-representations

  A curated list of resources on implicit neural representations.

  2.4k135

• KingJamesSong/latent-flow

  NeurIPS23 "Flow Factorized Representation Learning"

  Language:Python291

• LouisSerrano/coral

  Language:Jupyter Notebook234

• ASK-Berkeley/Neural-Spectral-Methods

  [ICLR 2024] Neural Spectral Methods: Self-supervised learning in the spectral domain.

  Language:Python282

• DreamFold/FoldFlow

  FoldFlow: SE(3)-Stochastic Flow Matching for Protein Backbone Generation

  Language:Jupyter Notebook1547

• mit-biomimetics/fld

  Repository for our paper: FLD: Fourier Latent Dynamics for Structured Motion Representation and Learning, Proceedings of the 12th International Conference on Learning Representations (ICLR)

  Language:Python22921

• crispitagorico/torchspde

  Neural Stochastic PDEs: resolution-invariant modelling of continuous spatiotemporal dynamics

  Language:Jupyter Notebook448

• optray/PIANO

  This repository contains the code for the paper: Deciphering and integrating invariants for neural operator learning with various physical mechanisms, National Science Review, 2024

  Language:Python11

• PredictiveIntelligenceLab/CausalPINNs

  Language:Jupyter Notebook13328

• neuraloperator/physics_informed

  Language:Python34182

• i207M/PINNacle

  Codebase for PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs.

  Language:Python20937

• dc3042/CROM_offline_training

  Language:Python204

• LeapLabTHU/ARC

  ICCV 2023: Adaptive Rotated Convolution for Rotated Object Detection

  Language:Python1013

• lu-group/deeponet-extrapolation

  DeepONet extrapolation

  Language:Python206

• Zymrael/awesome-neural-ode

  A collection of resources regarding the interplay between differential equations, deep learning, dynamical systems, control and numerical methods.

  1.3k146

• LeapLabTHU/LAUDNet

  IEEE TPAMI: Latency-aware Unified Dynamic Networks for Efficient Image Recognition

  Language:Jupyter Notebook402

• mkirchmeyer/DINo

  Time- and space-continuous neural PDE forecaster based on INRs and ODEs

  Language:Python467

• renatoberlinghieri/Helmholtz-GP

  Language:Jupyter Notebook71

• vc-bonn/Unsupervised_Deep_Learning_of_Incompressible_Fluid_Dynamics

  Language:Python9022

• cics-nd/ar-pde-cnn

  Physics-constrained auto-regressive convolutional neural networks for dynamical PDEs

  Language:Python8330

• pehersto/ng

  Neural Galerkin

  Language:Python131

• honglin-c/INSR-PDE

  Code for paper "Implicit Neural Spatial Representations for Time-dependent PDEs", ICML 2023

  Language:Python316

• LeapLabTHU/FLatten-Transformer

  Official repository of FLatten Transformer (ICCV2023)

  Language:Python37321

• LeapLabTHU/Dynamic_Perceiver

  Official implementation of Dynamic Perceiver

  Language:Python392

• amazon-science/probconserv

  Datasets and code for results presented in the ProbConserv paper

  Language:Python509

• PredictiveIntelligenceLab/Physics-informed-DeepONets

  Language:Jupyter Notebook26583

• deepchem/deepchem

  Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology

  Language:Python5.4k1.7k

• comp-physics/CPINN

  Competitive Physics Informed Networks

  Language:Python253

• mroberto166/wpinns

  Language:Python53

• thuml/Latent-Spectral-Models

  About Code Release for "Solving High-Dimensional PDEs with Latent Spectral Models" (ICML 2023), https://arxiv.org/abs/2301.12664

  Language:Python595