A method for conditional shapley value estimation, built off the shapr package: https://github.com/NorskRegnesentral/shapr/tree/master
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Updated
Jan 10, 2024 - R
A method for conditional shapley value estimation, built off the shapr package: https://github.com/NorskRegnesentral/shapr/tree/master
Explanations gain more and more attention in the context of explainable systems. This repo contains research about different aspects of explanations and how to integrate them in an existing system.
End-to-end ML: Using ML to generate expected PPS, opportunity grade classification, and prescription analysis for basketball coaches.
code for paper in NLDB'23
Extrapolation, using XGBoost, of the high-resolution seismic echo-classification into a bigger area (bathymetric surface along SBP data).
App for deriving local / global explanations of UMAP embeddings based on principal component analysis (PCA).
Classification model using Gradient Goosted Trees with feature selection and explainability
Contains the frontend and backend needed to execute the web app used to find anomalous behaviour in the decisions of a planning algorithm: POMCP
Optimising Rule Extraction for Deep Neural Networks. My third year university dissertation project
What and How of Machine Learning Transparency – ECML-PKDD 2020 Hands-on Tutorial
A doctoral dissertation titled "Towards the Advancement of Open-Domain Textual Question Answering Methods". The dissertation presents several innovative solutions aimed at addressing the challenges faced by ODQA systems and improving the performance.
Training and exploration of linear probes into Othello-GPT by Li et al. (2022)
Adaptation of the official PyTorch implementation for Transformer Interpretability Beyond Attention Visualization, a novel method to visualize classifications by Transformer based networks [CVPR 2021] to ESM.
Extracting finite state machine (Mealy Machine) from Recurrent Neural Networks (Many-to-Many)
This Tower of Hanoi Game Prototype is an attempt at explaining Q-learning and Reinforcement Learning Principles to People in an Intuitive and Interactive Way
Thesis project: "On the clinical acceptance of EEG seizure prediction methodologies". Explainability of seizure prediction models.
Interpretations on the HPA dataset.
One of the firsts dataset level explanability libraries for 1d signal using GRAD-CAM++
Code for the paper Tětková et al.: Knowledge Graphs for Empirical Concept Retrieval (accepted to The 2nd World Conference on eXplainable Artificial Intelligence).
Predict Man of the Match using various machine learning techniques and explain misclassifications
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