Name: SATYASARAN CHANGDAR
Type: User
Company: University of Copenhagen, Denmark
Bio: I am a postdoc @ UCPH, presently working on development of scientific machine learning methods for analysis of multi-modal data in Diary Industry and Agri!
Location: Copenhagen
Blog: https://satyasaran.github.io
SATYASARAN CHANGDAR's Projects
Enhancing PINNs for Solving PDEs via Adaptive Collocation Point Movement and Adaptive Loss Weighting
A list of popular deep learning models related to classification, segmentation and detection problems
A sample app for the Retrieval-Augmented Generation pattern running in Azure, using Azure Cognitive Search for retrieval and Azure OpenAI large language models to power ChatGPT-style and Q&A experiences.
Attention-Guided Version of 2D UNet for Automatic Brain Tumor Segmentation
Use of state of the art Convolutional neural network architectures including 3D UNet, 3D VNet and 2D UNets for Brain Tumor Segmentation and using segmented image features for Survival Prediction of patients through deep neural networks.
Deep Learning Based Solution of Nonlinear Partial Differential Equations Arising in the Process of Arterial Blood flow
A collection of useful scripts, templates, and examples for clusters using SLURM https://slurm.schedmd.com/
A GUI Tool for visualizing the intermediate layer of VGG-16 CNN trained on Imagenet
Deep root phenotyping using Deep Learning
Non-invasive phenotyping using Machine Learning
A library for scientific machine learning and physics-informed learning
Digital Imaging of Root Traits: Extract trait measurements from images of monocot and dicot roots.
gPINN: Gradient-enhanced physics-informed neural networks
keras implementation of gradcam_plus_plus
Unlock the full potential of your Apple Silicon-powered M3, M3 Pro, and M3 Max MacBook Pros by leveraging TensorFlow, the open-source machine learning framework. This repository is tailored to provide an optimized environment for setting up and running TensorFlow on Apple's cutting-edge M3 chips.
2nd place solution for the Kaggle Diabetic Retinopathy Detection Challenge
Deep Learning for humans
Machine learning for NeuroImaging in Python
Open standard for machine learning interoperability
Investigating PINNs
Physics-Informed Neural networks for Advanced modeling
Must-read Papers on Physics-Informed Neural Networks.
Applications of PINOs