Course project report and code for Geostatistics and Seabed Characterization

A deep-learning framework to map the benthic habitat distribution of the Mediterranean Sea.

🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models

Real-time Web Dashboard for Optuna.

Predicting likely 1D layer-depth sequences based on formations where lateral wells are typical

Deep Convolutional Neural Network for Automatic Fault Recognition from 3D Seismic Dataset

The repository includes PyTorch code, and the data, to reproduce the results for our paper titled "A Machine Learning Benchmark for Facies Classification" (published in the SEG Interpretation Journ…

Kaggle | 14th place solution for TGS Salt Identification Challenge

Geographic centroids with population weighing

the results, code and the data for the Force 2020 Machine learning competition after the completion of the competition in October 2020.

the results, code and the data for the Force 2020 Machine learning competition after the completion of the competition in October 2020.

Stop prompting. Start specifying.

Statistical detection tools for screening published research — spurious correlations, GRIMMER, p-value recomputation, power analysis, and more

Official Code of Memento: Fine-tuning LLM Agents without Fine-tuning LLMs

A python library for forgery detection in digital images

Optimizing Picobot solutions from Harvey Mudd's CS for All course (2015 → 2026)

Offshore wind power calculator using Ginsberg's Swept Area Method

Automagically remove trends from time-series data

ELM is a collection of utilities to apply Large Language Models (LLMs) to energy research.

Hackers' Guide to Language Models

A colormap for the color wheel

A Structured Output Framework for LLM Outputs

Simple, unified interface to multiple Generative AI providers

TimesFM (Time Series Foundation Model) is a pretrained time-series foundation model developed by Google Research for time-series forecasting.

Mirror of https://gitlab.windenergy.dtu.dk/TOPFARM/PyWake