Projects per year
Personal profile
Diplomas
Master's degree in philosophy (UCL, 2015)
Master's degree in computer science (UCL, 2013)
Bachelor's degree in computer science (UCL, 2011)
Diplomas
Master's degree in philosophy (UCL, 2015)
Master's degree in computer science (UCL, 2013)
Bachelor's degree in computer science (UCL, 2011)
Fingerprint Dive into the research topics where ADRIEN BIBAL is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
- 1 Similar Profiles
Network
Recent external collaboration on country level. Dive into details by clicking on the dots.
Projects
- 1 Active
VeriLearn: Verifying Learning Artificial Intelligence Systems
HEYMANS, P., FRENAY, B., SCHOBBENS, P., TEMPLE, P., Nanfack, G., AMRANI, M. & BIBAL, A.
1/01/18 → 31/12/21
Project: Research
Research Output
BIR: A Method for Selecting the Best Interpretable Multidimensional Scaling Rotation using External Variables
Marion, R., Bibal, A. & Frenay, B., 4 Feb 2019, In : Neurocomputing. 342, p. 83-96 14 p.Research output: Contribution to journal › Article
File
Measuring Quality and Interpretability of Dimensionality Reduction Visualizations
Bibal, A. & Frenay, B., 2019, SafeML ICLR Workshop. New Orleans, LouisianaResearch output: Contribution in Book/Catalog/Report/Conference proceeding › Conference contribution
Open Access
File
User-Based Experiment Guidelines for Measuring Interpretability in Machine Learning
Bibal, A., Dumas, B. & Frenay, B., 2019, EGC Workshop on Advances in Interpretable Machine Learning and Artificial Intelligence. MetzResearch output: Contribution in Book/Catalog/Report/Conference proceeding › Conference contribution
Open Access
File
Finding the Most Interpretable MDS Rotation for Sparse Linear Models based on External Features
Bibal, A., Marion, R. & Frenay, B., 1 Jan 2018, 26th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Bruges, p. 537-542 6 p. (ESANN 2018 - Proceedings, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning).Research output: Contribution in Book/Catalog/Report/Conference proceeding › Conference contribution
Open Access
File
Interpretability of Machine Learning Models and Representations: an Introduction
Bibal, A. & Frenay, B., 2016, 24th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Bruges, p. 77-82Research output: Contribution in Book/Catalog/Report/Conference proceeding › Conference contribution
Open Access
File