☆16Aug 28, 2024Updated last year
Alternatives and similar repositories for SuffixTransformerNetwork
Users that are interested in SuffixTransformerNetwork are comparing it to the libraries listed below
Sorting:
- Code for the paper "Predict-then-optimize or predict-and-optimize? An empirical evaluation of cost-sensitive learning strategies".☆19Feb 7, 2024Updated 2 years ago
- A process mining library built upon scikit-learn!☆22Oct 6, 2025Updated 5 months ago
- Stack't is a small MDS-in-a box, that specializes in providing interoperability for object-centric event logs by mapping to a flexible & …☆14Apr 26, 2025Updated 10 months ago
- CLI tool for automated discovery of BPS models from event logs☆50Jun 13, 2025Updated 9 months ago
- Amun is a framework that achieves privacy-preserving process mining using differential privacy.☆12Jan 16, 2023Updated 3 years ago
- Data Analysis Experiments☆12Nov 2, 2017Updated 8 years ago
- Carrot auto-writes specs and catches AI code drift. MCP server for Cursor that AST-validates every commit.☆29May 28, 2025Updated 9 months ago
- Transformer Network for Predictive Business Process Monitoring Tasks☆47Sep 26, 2024Updated last year
- This repository generates process mining event log features. Most of the features have been extracted from several process mining scienti…☆12Oct 28, 2021Updated 4 years ago
- ☆20Dec 8, 2021Updated 4 years ago
- ☆19Sep 10, 2019Updated 6 years ago
- A simple pytorch implementation for calculating VAE loss components and annealing KLD loss while training VAEs, especially RNN-based☆20Dec 26, 2024Updated last year
- Mixture of Decision Trees for Interpretable Machine Learning☆11Sep 2, 2021Updated 4 years ago
- Convex optimization for statistics and machine learning☆37Sep 11, 2025Updated 6 months ago
- Prescriptive business process monitoring for recommending next best actions (nba)☆32Dec 21, 2021Updated 4 years ago
- Business Process Encoding☆12Jul 9, 2024Updated last year
- Code for paper "Estimating Causal Effects on Networked Observational Data via Representation Learning"☆20May 28, 2023Updated 2 years ago
- Official implementation of Auxiliary learning as an Bargaining Game.☆32Jan 19, 2024Updated 2 years ago
- Pytorch implementation of "Diversified in-domain synthesis with efficient fine-tuning for few-shot classification"☆19Mar 25, 2024Updated last year
- Jupyter Widgets for interactive graphs powered by the Eclipse Layout Kernel (ELK)☆44Oct 31, 2024Updated last year
- A course on advanced object-oriented design and programming☆19Jan 12, 2026Updated 2 months ago
- a language model with gated conv nets (implements https://arxiv.org/pdf/1612.08083v1.pdf)☆16Jan 5, 2021Updated 5 years ago
- ☆12May 12, 2020Updated 5 years ago
- ☆22Jul 27, 2023Updated 2 years ago
- A Deep Learning model for business process predictions. Preprint on arXiv: https://arxiv.org/abs/2102.07838☆12Feb 2, 2021Updated 5 years ago
- TF2 implementation of "Attention, Learn to Solve Routing Problems!" (arXiv:1803.08475) article.☆40Jul 6, 2020Updated 5 years ago
- ☆13May 28, 2021Updated 4 years ago
- ☆13Sep 5, 2023Updated 2 years ago
- Implementation of the BP-MLL loss function in Tensorflow☆38Aug 10, 2019Updated 6 years ago
- ☆17Mar 12, 2026Updated last week
- ☆11Jul 11, 2022Updated 3 years ago
- Comparative experimental evaluation of outcome-oriented predictive monitoring techniques on a benchmark consisting of 24 real-world datas…☆33Apr 13, 2021Updated 4 years ago
- Tensorflow Implementation of "FNet: Mixing Tokens with Fourier Transforms."☆22May 22, 2021Updated 4 years ago
- Repository containing all implementations and experiments for the EDBN model.☆18Nov 9, 2021Updated 4 years ago
- An implementation of M5 and model trees in python, compliant with scikit-learn.☆24Jan 22, 2024Updated 2 years ago
- Repository containing code from team Kingsterdam for the Hateful Memes Challenge☆23Oct 24, 2022Updated 3 years ago
- PyTorch implementation for Neural Additive Models☆25Dec 2, 2020Updated 5 years ago
- Intro to Generative Adversarial Networks in Pytorch☆33Apr 25, 2019Updated 6 years ago
- Code for the WSDM '20 paper, Learning Individual Causal Effects from Networked Observational Data.☆78Jul 8, 2021Updated 4 years ago