Pinned Repositories
AgentLaboratory
Agent Laboratory is an end-to-end autonomous research workflow meant to assist you as the human researcher toward implementing your research ideas
AirfRANS
In this repository, you will find the different python scripts to train the available models on the AirfRANS dataset proposed at the NeurIPS 2022 Datasets and Benchmarks Track conference.
airfrans_lib
The AirfRANS dataset makes available numerical resolutions of the incompressible Reynolds-Averaged Navier–Stokes (RANS) equations over the NACA 4 and 5 digits series of airfoils and in a subsonic flight regime setup.
awesome-neural-ode
A collection of resources regarding the interplay between differential equations, deep learning, dynamical systems, control and numerical methods.
Basics_of_HPC_IIT_Goa
The example codes discussed in the course are available here.
bootcamp
Bootcamp notebooks
CAMLab-DLSCTutorials
ClimSim
An open large-scale dataset for training high-resolution physics emulators in hybrid multi-scale climate simulators.
Computational-Science-and-Engineering
18.085 Gilbert Strang Computational Science and Engineering
cs224n-win2223
Code and written solutions of the assignments of the Stanford CS224N: Natural Language Processing with Deep Learning course from winter 2022/2023
KulkarniHrishikesh's Repositories
KulkarniHrishikesh/bootcamp
Bootcamp notebooks
KulkarniHrishikesh/CAMLab-DLSCTutorials
KulkarniHrishikesh/ClimSim
An open large-scale dataset for training high-resolution physics emulators in hybrid multi-scale climate simulators.
KulkarniHrishikesh/deepmind-research
This repository contains implementations and illustrative code to accompany DeepMind publications
KulkarniHrishikesh/DLSC-2023
ETH Zürich Deep Learning in Scientific Computing Master's course 2023
KulkarniHrishikesh/DLSC_projects
This repository contains the machine learning projects completed for the class "Deep Learning in Scientific Computing" taught at ETH jointly by Siddhartha Mishra and Benjamin Moseley in Spring 2024. The description of the tasks can be found in the PDFs.
KulkarniHrishikesh/sciann
Deep learning for Engineers - Physics Informed Deep Learning
KulkarniHrishikesh/SciMLBook
Parallel Computing and Scientific Machine Learning (SciML): Methods and Applications (MIT 18.337J/6.338J)
KulkarniHrishikesh/deepxde
A library for scientific machine learning and physics-informed learning
KulkarniHrishikesh/DrivAerNet
A Large-Scale Multimodal Car Dataset with Computational Fluid Dynamics Simulations and Deep Learning Benchmarks
KulkarniHrishikesh/fastvpinns
FastVPINNs - A tensor-driven acceleration of VPINNs for complex geometries
KulkarniHrishikesh/FluidX3D
The fastest and most memory efficient lattice Boltzmann CFD software, running on all GPUs via OpenCL. Free for non-commercial use.
KulkarniHrishikesh/graph-pde
Using graph network to solve PDEs
KulkarniHrishikesh/jaxpi
KulkarniHrishikesh/LIPS
KulkarniHrishikesh/Lorenz96
Understanding Lorentz96 One and Two layer systems
KulkarniHrishikesh/markov_neural_operator
KulkarniHrishikesh/modulus
Open-source deep-learning framework for building, training, and fine-tuning deep learning models using state-of-the-art Physics-ML methods
KulkarniHrishikesh/neural-ode
Jupyter notebook with Pytorch implementation of Neural Ordinary Differential Equations
KulkarniHrishikesh/neurodiffeq
A library for solving differential equations using neural networks based on PyTorch, used by multiple research groups around the world, including at Harvard IACS.
KulkarniHrishikesh/neuromancer
Pytorch-based framework for solving parametric constrained optimization problems, physics-informed system identification, and parametric model predictive control.
KulkarniHrishikesh/PaddleScience
PaddleScience is SDK and library for developing AI-driven scientific computing applications based on PaddlePaddle.
KulkarniHrishikesh/PhiFlow
A differentiable PDE solving framework for machine learning
KulkarniHrishikesh/Physics-Informed-Neural-Networks-for-Quantum-Dynamics
A repo to learn and curate PINN
KulkarniHrishikesh/physics_informed_NO
KulkarniHrishikesh/pptale.github.io
MNA_course
KulkarniHrishikesh/PyDMD
Python Dynamic Mode Decomposition
KulkarniHrishikesh/pykoopman
A package for computing data-driven approximations to the Koopman operator.
KulkarniHrishikesh/TeachingDataScience
Course notes for Data Science related topics, prepared in LaTeX
KulkarniHrishikesh/torchdiffeq
Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.