acse-sl420

18337

18.337 - Parallel Computing and Scientific Machine Learning

18S096SciML

18.S096 - Applications of Scientific Machine Learning

acse-9-independent-research-project-kmei92

acse-9-independent-research-project-kmei92 created by GitHub Classroom

AutoML-Tutorial

Tutorials about AutoML

iTransformer

Implementation of iTransformer - SOTA Time Series Forecasting using Attention networks, out of Tsinghua / Ant group

jax-fenics-adjoint

Differentiable interface to FEniCS/Firedrake for JAX using dolfin-adjoint/pyadjoint

meshGraphNets_pytorch

PyTorch implementations of Learning Mesh-based Simulation With Graph Networks

MrCAE

a multiresolution convolutional autoencoder architecture

Turbulent-Flow-Net

YouGraph

graph learning code for ogb

acse-sl420/iTransformer

Implementation of iTransformer - SOTA Time Series Forecasting using Attention networks, out of Tsinghua / Ant group

acse-sl420/jax-fenics-adjoint

Differentiable interface to FEniCS/Firedrake for JAX using dolfin-adjoint/pyadjoint

acse-sl420/ampnet

Attention as Message Passing for Graph Neural Networks

acse-sl420/awesome-graph-ood

Papers about out-of-distribution generalization on graphs.

acse-sl420/Awesome-Transformer-Attention

An ultimately comprehensive paper list of Vision Transformer/Attention, including papers, codes, and related websites

acse-sl420/BSMS-GNN

acse-sl420/DAGNN

A graph neural network tailored to directed acyclic graphs that outperforms conventional GNNs by leveraging the partial order as strong inductive bias besides other suitable architectural features.

acse-sl420/Deep-Reinforcement-Learning-Algorithms-with-PyTorch

PyTorch implementations of deep reinforcement learning algorithms and environments

acse-sl420/deepchem

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

acse-sl420/DIFFormer

The official implementation for ICLR23 spotlight paper "DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion"

acse-sl420/DRew

acse-sl420/floris

FLORIS with different orientation

acse-sl420/fourier-neural-operator

acse-sl420/GINR

Code for "Generalised Implicit Neural Representations" (NeurIPS 2022).

acse-sl420/HiMol

acse-sl420/interpretable_gnn

acse-sl420/megnet

Graph Networks as a Universal Machine Learning Framework for Molecules and Crystals

acse-sl420/MeshDQN

Using deep reinforcement learning for refining meshes in computational fluid dynamics

acse-sl420/MolCLR

Implementation of MolCLR: "Molecular Contrastive Learning of Representations via Graph Neural Networks" in PyG.

acse-sl420/NASA_Li-ion_Battery_SOH_Prediction_with_MVIP-Trans

This research provides a prognostic framework for off-line SOH estimation of Li-ion battery. With a CNN-Transformer architecture, this program is capable of modeling the temporal correlations of battery signals from both local and global views. In this way, the learning ability of both local features and long period contexts will be enhanced.

acse-sl420/NodeFormer

The official implementation of NeurIPS22 spotlight paper "NodeFormer: A Scalable Graph Structure Learning Transformer for Node Classification"

acse-sl420/probing-graph-transformers

Code for our paper "Attending to Graph Transformers"

acse-sl420/PyTorch-DDPM

500 行代码实现降噪扩散模型 DDPM，干净无依赖

acse-sl420/pytorch-Deep-Learning

Deep Learning (with PyTorch)

acse-sl420/sd-vae

Code for the paper "Disentangled Generative Models for Robust Prediction of System Dynamics"

acse-sl420/SGFormer

acse-sl420/summer-school-2023

acse-sl420/TFDSUNet

TFDSUNet: Time-Frequency Dual-Stream Uncertainty Network for Battery SOH/SOC Prediction

acse-sl420/tokengt

[NeurIPS'22] Tokenized Graph Transformer (TokenGT), in PyTorch

acse-sl420/transformers