| 2026 | ESANN | Interpretable Parametric Neighbour Embedding. | Edouard Couplet, Pierre Lambert, Michel Verleysen, John A. Lee, Cyril de Bodt |
| 2026 | ESANN | Multi-Scale Stochastic Neighbor Embedding with Twice Adaptive Bandwidths. | John A. Lee, Pierre Lambert, Edouard Couplet, Pierre Merveille, Dounia Mulders, Cyril de Bodt, Michel Verleysen |
| 2025 | ESANN | Can MDS rival with t-SNE by using the symmetric Kullback-Leibler divergence\\ across neighborhoods as a pseudo-distance? | John A. Lee, Pierre Lambert, Edouard Couplet, Pierre Merveille, Ludovic Journaux, Dounia Mulders, Cyril de Bodt, Michel Verleysen |
| 2024 | ESANN | Forget early exaggeration in t-SNE: early hierarchization preserves global structure. | John A. Lee, Edouard Couplet, Pierre Lambert, Ludovic Journaux, Dounia Mulders, Cyril de Bodt, Michel Verleysen |
| 2024 | ESANN | Estimated neighbour sets and smoothed sampled global interactions are sufficient for a fast approximate tSNE. | Pierre Lambert, Edouard Couplet, Cyril de Bodt, John A. Lee |
| 2023 | ESANN | On the number of latent representations in deep neural networks for tabular data. | Edouard Couplet, Pierre Lambert, Michel Verleysen, John A. Lee, Cyril de Bodt |
| 2023 | ESANN | Nesterov momentum and gradient normalization to improve t-SNE convergence and neighborhood preservation, without early exaggeration. | Pierre Lambert, John A. Lee, Edouard Couplet, Cyril de Bodt |