1710293276

1710293276's Stars

• xzhou99/DTALite-S

  Simplified Version of DTALite for Education and Research

  Language:C++189

• Lucky-Fan/GP_TSE

  Language:Jupyter Notebook71

• giuliamesc/BPINNs

  Language:Python167

• ekinugurel/physics-regularized-MTGP

  Includes codes for the forthcoming paper, "Learning to generate synthetic human mobility data: A physics-regularized Gaussian process approach based on multiple kernel learning"

  Language:Jupyter Notebook2

• marvinpfoertner/linpde-gp

  Code for the Paper "Physics-Informed Gaussian Process Regression Generalizes Linear PDE Solvers"

  Language:Python213

• labmlai/annotated_deep_learning_paper_implementations

  🧑‍🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

  Language:Python54.5k5.6k

• pnnl/neuromancer

  Pytorch-based framework for solving parametric constrained optimization problems, physics-informed system identification, and parametric model predictive control.

  Language:Python886116

• pabloguarda/isuelogit

  Inverse Stochastic User Equilibrium with LOGIT assignment

  Language:Jupyter Notebook101

• Urbanity-Lab/PIDL-PSO

  Physics Informed Deep Learning (PIDL) with Particle Swarm Optimization (PSO) for Traffic State Estimation

  2

• arjhuang/pise

  Physics Informed Deep Learning for Traffic State Estimation: Illustrations with LWR and CTM Models

  Language:Python135

• maziarraissi/PINNs

  Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations

  Language:Python3.7k1.3k

• Urbanity-Lab/PIDL

  Physics Informed Deep Learning - Traffic State Estimation

  Language:Python163

• long-da/A-United-Framework-to-Integrate-Physics-into-Gaussian-Processes

  Language:Python82

• ziatdinovmax/AugmentedGaussianProcess

  Gaussian process augmented with a probabilistic model of expected system's behavior

  Language:Jupyter Notebook12

• junjun-yan/ST-PINN

  A Self-Training Physics-Informed Neural Network for Partial Differential Equations

  Language:Python181

• JinshuaiBai/PIRBN

  Physics-informed radial basis network

  Language:Python256

• bentrevett/pytorch-seq2seq

  Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.

  Language:Jupyter Notebook5.3k1.3k

• jayhack/LSTMVRAE

  Variational Recurrent Auto-Encoder using LSTM encoder/decoder networks

  Language:Python5414

• RobertKrajewski/highD-dataset

  Language:MATLAB19084

• guillaume-chevalier/seq2seq-signal-prediction

  Signal forecasting with a Sequence-to-Sequence (seq2seq) Recurrent Neural Network (RNN) model in TensorFlow - Guillaume Chevalier

  Language:Jupyter Notebook1.1k294

• shu-hai/D-GCCA

  Decomposition-based Generalized Canonical Correlation Analysis for Multi-view High-dimensional Data (JMLR-22 paper)

  Language:Python41

• mbrbic/Multi-view-LRSSC

  Matlab implementation of multi-view low-rank sparse subspace clustering

  Language:MATLAB5329

• Lemma1/Probabilistic-OD-Estimation

  Estimating probabilistic dynamic origin-destination demands

  Language:Python6

• Lemma1/MAC-POSTS

  Mobility Data Analytics Center - Prediction, Optimization, and Simulation toolkit for Transportation Systems

  Language:Jupyter Notebook2019

• sakithakumarage/hybrid_DODE

  A hybrid modelling framework for the estimation of dynamic origin-destination flows

  Language:MATLAB31

• mcgill-smart-transport/high-order-weighted-DMD

  Language:Jupyter Notebook9

• salomonw/Price_of_Anarchy_for_Transportation_Networks

  Data-Driven Price of Anarchy Estimation using Inverse Optimization

  Language:Jupyter Notebook42

• jingzbu/InverseVIsTraffic

  Inverse Variational Inequalities along with optimization problems arising in Traffic networks

  Language:Jupyter Notebook263

• danielrherber/admm-qp

  Language:Matlab126

• Chengyuan-Zhang/IDM_Bayesian_Calibration

  Language:Jupyter Notebook323