2 Search Results for "Noutahi, Emmanuel"


Document
D-GRIL: End-To-End Topological Learning with 2-Parameter Persistence

Authors: Soham Mukherjee, Shreyas N. Samaga, Cheng Xin, Steve Oudot, and Tamal K. Dey

Published in: LIPIcs, Volume 367, 42nd International Symposium on Computational Geometry (SoCG 2026)


Abstract
End-to-end topological learning using 1-parameter persistence is well-known. We show that the framework can be enhanced using 2-parameter persistence by adopting a recently introduced 2-parameter persistence based vectorization technique called Gril. We establish a theory for gradient descent on Gril producing D-Gril. We show that D-Gril can be used to learn a bifiltration function on benchmark graph datasets. Further, we exhibit that this framework can be applied in the context of bio-activity prediction in drug discovery.

Cite as

Soham Mukherjee, Shreyas N. Samaga, Cheng Xin, Steve Oudot, and Tamal K. Dey. D-GRIL: End-To-End Topological Learning with 2-Parameter Persistence. In 42nd International Symposium on Computational Geometry (SoCG 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 367, pp. 79:1-79:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)


Copy BibTex To Clipboard

@InProceedings{mukherjee_et_al:LIPIcs.SoCG.2026.79,
  author =	{Mukherjee, Soham and Samaga, Shreyas N. and Xin, Cheng and Oudot, Steve and Dey, Tamal K.},
  title =	{{D-GRIL: End-To-End Topological Learning with 2-Parameter Persistence}},
  booktitle =	{42nd International Symposium on Computational Geometry (SoCG 2026)},
  pages =	{79:1--79:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-418-5},
  ISSN =	{1868-8969},
  year =	{2026},
  volume =	{367},
  editor =	{Ahn, Hee-Kap and Hoffmann, Michael and Nayyeri, Amir},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SoCG.2026.79},
  URN =		{urn:nbn:de:0030-drops-258865},
  doi =		{10.4230/LIPIcs.SoCG.2026.79},
  annote =	{Keywords: Topological Data Analysis, Persistent Homology, Multiparameter Persistence, Graph Learning, Graph Neural Networks}
}
Document
Efficient Non-Binary Gene Tree Resolution with Weighted Reconciliation Cost

Authors: Manuel Lafond, Emmanuel Noutahi, and Nadia El-Mabrouk

Published in: LIPIcs, Volume 54, 27th Annual Symposium on Combinatorial Pattern Matching (CPM 2016)


Abstract
Polytomies in gene trees are multifurcated nodes corresponding to unresolved parts of the tree, usually due to insufficient differentiation between sequences of homologous gene copies. Apart from gene sequences, other information such as that contained in the species tree can be used to resolve such intricate parts of a gene tree. The problem of resolving a multifurcated tree has been considered by many authors, the objective function often being the number of duplications and losses reflected by the reconciliation of the resolved gene tree with the species tree. Here, we present PolytomySolver, an algorithm accounting for a more general model allowing different costs for duplications and losses per species. The time complexity of this algorithm is linear for the unit cost and is quadratic for the general cost, which outperforms the best known solutions so far by a linear factor. We show on simulated trees that the gain in theoretical complexity has a real practical impact on running times.

Cite as

Manuel Lafond, Emmanuel Noutahi, and Nadia El-Mabrouk. Efficient Non-Binary Gene Tree Resolution with Weighted Reconciliation Cost. In 27th Annual Symposium on Combinatorial Pattern Matching (CPM 2016). Leibniz International Proceedings in Informatics (LIPIcs), Volume 54, pp. 14:1-14:12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)


Copy BibTex To Clipboard

@InProceedings{lafond_et_al:LIPIcs.CPM.2016.14,
  author =	{Lafond, Manuel and Noutahi, Emmanuel and El-Mabrouk, Nadia},
  title =	{{Efficient Non-Binary Gene Tree Resolution with Weighted Reconciliation Cost}},
  booktitle =	{27th Annual Symposium on Combinatorial Pattern Matching (CPM 2016)},
  pages =	{14:1--14:12},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-012-5},
  ISSN =	{1868-8969},
  year =	{2016},
  volume =	{54},
  editor =	{Grossi, Roberto and Lewenstein, Moshe},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CPM.2016.14},
  URN =		{urn:nbn:de:0030-drops-60907},
  doi =		{10.4230/LIPIcs.CPM.2016.14},
  annote =	{Keywords: gene tree, polytomy, reconciliation, resolution, weighted cost, phylogeny}
}
  • Refine by Type
  • 2 Document/PDF
  • 1 Document/HTML

  • Refine by Publication Year
  • 1 2026
  • 1 2016

  • Refine by Author
  • 1 Dey, Tamal K.
  • 1 El-Mabrouk, Nadia
  • 1 Lafond, Manuel
  • 1 Mukherjee, Soham
  • 1 Noutahi, Emmanuel
  • Show More...

  • Refine by Series/Journal
  • 2 LIPIcs

  • Refine by Classification
  • 1 Computing methodologies → Machine learning
  • 1 Mathematics of computing → Algebraic topology

  • Refine by Keyword
  • 1 Graph Learning
  • 1 Graph Neural Networks
  • 1 Multiparameter Persistence
  • 1 Persistent Homology
  • 1 Topological Data Analysis
  • Show More...

Any Issues?
X

Feedback on the Current Page

CAPTCHA

Thanks for your feedback!

Feedback submitted to Dagstuhl Publishing

Could not send message

Please try again later or send an E-mail