All software
Supplementary code to the paper: Flexible Enterprise Optimization With Constraint Programming
Supplementary code to the paper: Flexible Enterprise Optimization With Constraint Programming
- Constraint programming (Computer science)
- deep learning
- Enterprise engineering
- + 2
trtpi
Code underlying the publication: Trust-Region Twisted Policy Improvement
- Autonomous Path-Planning
- deep learning
- Markov decision process
- + 2
- ("Jupyter Notebook")
- (Markdown)
- (Other)
- + 3
ClimaNet
A Climate Aware Spatio Temporal Encoder Decoder
- Big data
- climate
- deep learning
- ("Jupyter Notebook")
- (Python)
- (Shell)
CoeusAI
The CoeusAI QGIS plugin is designed for exploration of multiband geospatial datasets. It lets the user iteratively train and retrain segmentation models in seconds. A combination of Deep learning and traditional machine learning is used, leveraging the best of both methods.
- deep learning
- gis
- Machine learning
- + 2
- (Python)
diffWOFOST
The python package diffWOFOST is a differentiable implementation of WOFOST models using torch, allowing gradients to flow through the simulations for optimization and data assimilation.
- Data Analysis
- deep learning
- High performance computing
- + 2
- (Python)
document-segementation
Tool for identifying document boundaries and categories from VoC inventories.
- AI
- deep learning
- Machine learning
- + 2
- ("Jupyter Notebook")
- (Python)
EEG_age_prediction
Deep learning for age prediction using EEG data
- deep learning
- EEG Signal
- Time Series
- ("Jupyter Notebook")
- (Python)
- (Shell)
2025-stereograph
This repository contains pre-trained models, computed results, and analysis code for evaluating machine learning approaches (Random Forests, FCNs, and GNNs) on gamma-ray event reconstruction tasks.
- Astroparticle physics
- cta
- deep learning
- + 2
- (Shell)
CTLearn: Deep learning for imaging atmospheric Cherenkov telescopes event reconstruction
CTLearn is a high-level Python package providing a backend for training deep learning models for the reconstruction of imaging atmospheric Cherenkov telescope events using TensorFlow.
- deep learning
- Event reconstruction
- High energy physics
- + 1
- (Dockerfile)
- ("Jupyter Notebook")
- (Python)
GammaLearn
GammaLearn is a collaborative project to apply deep learning to the analysis of low-level Imaging Atmospheric Cherenkov Telescopes such as CTA. It provides a framework to easily train and apply models from a configuration file. Learn more at https://purl.org/gammalearn
- cta
- deep learning
- Gamma-ray telescopes
- + 1
- (Dockerfile)
- (Python)
Introduction to deep learning lesson
This lesson gives an introduction to deep learning.
- deep learning
- lesson
- python
- ("Jupyter Notebook")
- (Makefile)
- (Python)
- + 1
NeuroGym
NeuroGym is a curated collection of neuroscience tasks with a common interface. The goal is to facilitate the training of neural network models on neuroscience tasks.
- deep learning
- Machine learning
- Neuroscience
- + 3
- (Python)