JamesMarshall31 / design-of-experimentsView external linksLinks
A Python Package for intuitive design of experiments with user-friendly analysis of results. The aim is for this package to rival the DOE capabilities of commercial software such as JMP. Currently designs and analysis will be more geared towards investigations following the Response Surface Methodology.
☆22Nov 5, 2020Updated 5 years ago
Alternatives and similar repositories for design-of-experiments
Users that are interested in design-of-experiments are comparing it to the libraries listed below
Sorting:
- DoEgen: A Python Library for Optimised Design of Experiment Generation and Evaluation☆99Apr 24, 2025Updated 9 months ago
- Deep Learning Scaling tutorial material for the Deep Learning for Science School at Berkeley Lab☆10Jul 19, 2019Updated 6 years ago
- A simple wrapper for python-bioformats to convert .vsi CellSense format to TIFF.☆12Apr 9, 2022Updated 3 years ago
- MCP server for org-mode and org-roam knowledge base management☆26Updated this week
- NOMU: Neural Optimization-based Model Uncertainty☆10Feb 17, 2023Updated 3 years ago
- Geometric Superpixel Representations for Efficient Image Classification with Graph Neural Networks☆13Aug 10, 2023Updated 2 years ago
- Text Detection by RetinaNet with PyTorch (Code will be released soon)☆10Dec 1, 2018Updated 7 years ago
- Stereographically Projected Cosmological Simulations☆13Updated this week
- Design-of-experiment (DOE) generator for science, engineering, and statistics☆280Apr 3, 2024Updated last year
- Design of Experiments for Python☆299Updated this week
- Use Gaussian processes to estimate CNN classification uncertainty☆12Mar 3, 2018Updated 7 years ago
- Neural network loss functions for regression and classification tasks that can say "I don't know".☆13Dec 2, 2021Updated 4 years ago
- ☆14Nov 17, 2023Updated 2 years ago
- ☆10Jan 24, 2020Updated 6 years ago
- ☆13Jan 21, 2026Updated 3 weeks ago
- A suite of tools for text preparation, vectorization and processing for deep learning with Keras.☆13Jul 29, 2023Updated 2 years ago
- KERL: reinforcement learning algorithms and tools implemented using Keras☆11Aug 2, 2024Updated last year
- Exploit Auto-encoder for exploring and predict flow dynamic☆10Oct 4, 2019Updated 6 years ago
- Active Learning in the era of Foundation Models☆12Apr 16, 2025Updated 10 months ago
- Bayesian time-difference-of-arrival positioning using pymc3☆15Dec 20, 2019Updated 6 years ago
- Tools for basic signal processing in epidemiology☆12Updated this week
- Imperial College Storm Model☆15May 5, 2024Updated last year
- A data transformation package for deep learning with Autonomio, Keras and TensorFlow.☆16Apr 20, 2024Updated last year
- Learn about designing and training LLM Agents from Colab Notebooks☆16Jun 6, 2025Updated 8 months ago
- NeurIPS 2020☆16Jun 18, 2021Updated 4 years ago
- Mission planning instrument tools for pysat☆13Jan 13, 2025Updated last year
- Code to replicate the simulation study in the paper "Calibrating doubly-robust estimators with unbalanced treatment assignment"☆15May 20, 2024Updated last year
- A Python package for working with OpenFOAM.☆15Oct 2, 2024Updated last year
- causal inference in python, have been reading judea pearl's book of why☆16Nov 12, 2018Updated 7 years ago
- ☆16Jul 11, 2023Updated 2 years ago
- Source code for deep learning-based reduced order models in cardiac electrophysiology. Available on doi.org/10.1371/journal.pone.0239416.☆16Sep 7, 2023Updated 2 years ago
- Code for NeurIPS'23 paper "A Bayesian Approach To Analysing Training Data Attribution In Deep Learning"☆17Jan 12, 2024Updated 2 years ago
- UNMAINTAINED AND PROBABLY NOT WORKING ANYMORE. PLEASE USE PROJ4 INSTEAD. Collection of (stereographic) map/coordinate projections.☆14May 25, 2020Updated 5 years ago
- A Keras implementation of DeepMask based on NIPS 2015 paper "Learning to Segment Object Candidates"☆15May 12, 2018Updated 7 years ago
- This is a repository of my python notebooks that may be of general interest.☆19Jan 29, 2025Updated last year
- Atmospheric River Detection Algorithm. Kennett (2021).☆21Aug 15, 2021Updated 4 years ago
- GNNs to predict wind farm-wide power, local flow variables and damage-equivalent loads.☆23Jul 7, 2025Updated 7 months ago
- Code for PCMCI-Ω algorithm from the NeurIPS'23 paper "Causal Discovery in Semi-Stationary Time Series"☆18Oct 16, 2024Updated last year
- ☆15Jun 2, 2022Updated 3 years ago