Some recent (and less recent) talks
Rome Centre on Mathematics for Modelling and Data ScienceS, Università di Roma "Tor Vergata", 20 marzo 2024,
Osservazioni geometriche per l'intelligenza artificiale. Knowledge and Cognition Seminar Series, Research Center Knowledge and Cognition, Bologna, 6 marzo 2024,
Osservazioni geometriche sull'apprendimento automatico e l'intelligenza artificiale. International Conference on Mathematics for Data Science & Dynamics-2024 (ICMDD-2024) & Annual Conference of Kerala Mathematical Association, Rajagiri School of Engineering & Technology, Kochi, Kerala, INDIA, February 1-3, 2024,
Some recent advances in the theory of equivariant non-expansive operators and its application to Machine Learning. Convegno "L’opera matematica di Betti, ieri e oggi", Scuola Normale Superiore, Pisa, 20 ottobre 2023,
Un'escursione dai numeri di Betti al deep learning geometrico passando per l'omologia persistente e l'analisi topologica dei dati. "Matematica per l’Intelligenza Artificiale e il Machine Learning", Congresso UMI 2023, Pisa, 7 settembre 2023,
Dallo studio dell’insieme dei dati
all’analisi dello spazio degli osservatori:
come la geometria degli operatori equivarianti non espansivi
può aiutarci nell’interpretazione delle informazioni. 10th International Congress on Industrial and Applied Mathematics (ICIAM 2023), Waseda University, Tokyo, Japan, August 20 - 25, 2023,
Equivariant non-expansive operators as a bridge between TDA and geometric deep learning. CaLISTA kick-off meeting, Bologna, 5-9 June 2023,
Recent advances in the theory of GENEOs and its application to Machine Learning.
“Coloquio CIMAT-DEMAT” - Guanajuato, Estado de Guanajuato, México, May 24, 2023,
On GENEOs and their application to Machine Learning.
Talk at the Department of Mathematics, University of Pisa, May 9, 2023, Topological data analysis as a bridge to geometric deep learning.
“Online Machine Learning Seminar” - School of Mathematical Sciences, University of Nottingham, March 22, 2023,
Some recent results on the theory of GENEOs and its application to Machine Learning. “Geometry of Deep Learning” - Ph.D. Course,
CaLIGOLA Training School, FIM, Modena, February 23, 2023,
From analyzing data to studying observers:
a journey through four recent papers. International Conference on Mathematics of Intelligent Computing and Data Science, Rajagiri School of Engineering & Technology, Kochi, Kerala, INDIA, September 15, 2022,
Approaching topological data analysis and geometric deep learning through group equivariant non-expansive operators. 8th International Workshop "Image Mining. Theory and Applications", August 21, 2022,
A new approach to topological data analysis and geometric deep learning through group equivariant
non-expansive operators. Conference on Applied, Combinatorial and Toric Topology, July 18-22, 2022, On the use of group equivariant non-expansive operators for topological data analysis and geometric deep learning. Talk at the MACHINE LEARNING GENOA CENTER, April 11, 2022, Some recent results on the use of group equivariant non-expansive operators for topological data analysis and geometric deep learning.
VIDEO OF THE TALK Webinar "Seminari su Intelligenza Artificiale e Machine Learning, Gruppo UMI “AI&ML&MAT", 4 marzo 2022, Sull’uso di operatori equivarianti non espansivi per
l’apprendimento automatico (Italian). Webinar "Big Data challenges for Mathematics: state of the art and future perspectives", February 25, 2022, On the use of group equivariant non-expansive operators for topological data analysis and geometric deep learning. International Conference on "Methods and Applications of Artificial Intelligence and Machine Learning in Heterogeneous Brains", September 4-6, 2021, Some recent results in the geometric-topological theory of group equivariant non-expansive operators. Online Workshop "Beyond TDA – Persistent topology and its applications in data sciences", NTU, August 28-30, 2021, On the role of group equivariant non-expansive operators in Topological Data Analysis. Serie di seminari dell'Istituto per le Applicazioni del Calcolo del CNR: "AIM: Artificial Intelligence and Mathematics, fundamentals and beyond", 9 Marzo 2021,
Osservazioni geometriche per l'intelligenza artificiale (Italian). Webinar Series: Topology, Rajagiri School of Engineering & Technology, September 25, 2020,
An introduction to topological data analysis through the
concepts of natural pseudo-distance, persistence diagram and
group equivariant non-expansive operator. Complex Simplex: Topological and Network Data Science Workshop, Politecnico di Torino, October 14-15, 2019,
Deep learning and group equivariant (non-expansive)
operators - Theory. (Joint presentation with Mattia G. Bergomi). Topological data analysis and deep learning: theory and signal applications, 9th International Congress on Industrial and Applied Mathematics, Valencia, Spain, July 15, 2019,
The theory of group equivariant non-expansive operators as a possible bridge between TDA and Deep Learning . International Workshop and Conference on Topology & Applications, Rajagiri School of Engineering & Technology, Kochi, Kerala, INDIA, December 5-11, 2018,
Some new results in 2D persistent homology . Please also download
this video illustrating the monodromy phenomenon in 2D persistent homology.
International Workshop and Conference on Topology & Applications, Rajagiri School of Engineering & Technology, Kochi, Kerala, INDIA, December 5-11, 2018,
The use of group equivariant non-expansive operators in
topological data analysis .
International Workshop and Conference on Topology & Applications, Rajagiri School of Engineering & Technology, Kochi, Kerala, INDIA, December 5-11, 2018,
The natural pseudo-distance in topological data analysis .
10th Conference on Geometric and Topological Methods in Computer Science (GETCO),
Oaxaca, Mexico, September 10-14, 2018,
The theory of group equivariant non-expansive operators in topological data analysis .
XXI BRAZILIAN TOPOLOGY MEETING,
Satellite conference of ICM 2018,
Universidade Federal Fluminense (Niterói, Rio de Janeiro, Brazil), August 12-18, 2018,
New advances in 2D sublevel set persistent homology
(video) .
Workshop on Homotopy Probability Theory,
Universität des Saarlandes (Saarbrücken, Germany), September 4-8, 2017,
Some advances in the application of group-invariant
persistent homology to topological data analysis .
Workshop on Homotopy Probability Theory,
Universität des Saarlandes (Saarbrücken, Germany), September 4-8, 2017,
An approach to topological data analysis via persistent
topology and invariant operators .
Mini course "Some new results in two-dimensional and group-invariant persistent homology", Ohio State University, April 3-7, 2017,
Lecture 3: Group-invariant persistent homology and its use for
topological data analysis
.
Mini course "Some new results in two-dimensional and group-invariant persistent homology", Ohio State University, April 3-7, 2017,
Lecture 2: The coherent matching distance in 2D persistent homology .
TGDA Seminar, Ohio State University, April 5, 2017,
A theoretical framework for topological data analysis .
Mini course "Some new results in two-dimensional and group-invariant persistent homology", Ohio State University, April 3-7, 2017,
Lecture 1: The phenomenon of monodromy in 2D persistent homology .
Computational Topology in Image Context,
Marseille, June 15-17, 2016,
The coherent matching distance in 2D persistent homology
(A more detailed version is available here SIAM Conference on Imaging Science,
Geometry-based Models in Image Processing, Albuquerque, 24 May 2016,
Image comparison via group invariant non-expansive operators .
9th Eurographics Workshop on 3D Object Retrieval,
Lisbon, 8 May 2016,
Towards an observer-oriented theory of shape comparison .
Segunda Escuela/Conferencia de Análisis Topológico de Datos, Querétaro, December 7-11, 2015,
An observer-oriented approach to topological data analysis. Part 1: From comparing subsets of R^n to studying metric spaces of functions .
Segunda Escuela/Conferencia de Análisis Topológico de Datos, Querétaro, December 7-11, 2015,
An observer-oriented approach to topological data analysis. Part 2: The algebra of group invariant non-expansive operators and its application in the project GIPHOD - Group Invariant Persistent Homology Online Demonstrator .
Geometric and Topological Methods in Computer Science, Aalborg, April 7-10, 2015,
Geometric shape comparison via G-invariant non-expansive
operators and G-invariant persistent homology .
Homology: Theoretical and Computational Aspects, Genoa, February 9-13, 2015,
G-invariant persistent homology .
Applied and Computational Algebraic Topology, Bremen, July 15-19, 2013,
Adapting persistent homology to invariance groups .
ACA 2013 - Special Session on Computer algebra
in algebraic topology and its applications, Málaga, July 3, 2013,
Some advances in G-invariant persistent topology and homology .
Seminar on "Topics in Mathematics" - Ph.D. Program in Mathematics (University of Bologna), 11 April 2013,
A quick trip through geometrical shape comparison .
Seminar on Computational Mathematics, Institute of Computer Science,
Jagiellonian University, Kraków, Poland, 25 October 2012,
A general distance for geometrical shape comparison .
Fifth Workshop on
Non-Rigid Shape Analysis and Deformable Image Alignment (in conjunction with ECCV 2012), Florence, Italy, 7 October 2012,
A metric paradigm for geometrical shape comparison .
Mini-symposium on Applied and Computational Algebraic Topology, 6ECM, Kraków, Poland,
4 July 2012,
Metric shape comparison via multidimensional persistent homology .
Dagstuhl Seminar “Applications of Combinatorial Topology to Computer Science”,
LZI Schloss Dagstuhl, Germany,
18-23 March 2012,
Some research notes on
G-invariant Persistent Homology .
Workshop on Computational Topology, Fields Institute, Toronto,
7-11 November 2011,
Filtrations induced by continuous functions .
Applied Algebraic Topology, ETH Zürich,
4-8 July 2011,
Some new results
in multidimensional persistent homology .
Third International Conference on Scale Space and Variational
Methods in Computer Vision,
Ein Gedi Resort, Dead Sea, Israel,
29 May - 2 June 2011,
Counting components of multi-dimensional
sub-level sets for shape comparison .
Colloquium on Computer Graphics,
PRIP - Vienna University of Technology,
17 December 2010,
A metric approach to shape comparison via
multidimensional persistence .
Geometric and Topological Methods in Computer Science,
Aalborg University, January 11-15, 2010,
Multidimensional persistent topology as a
metric approach to shape comparison .
Gilles Fournier Memorial Conference on Classical
and Computational Topological Methods,
Université de Sherbrooke, Canada, September 22-24, 2006,
Shape comparison by multidimensional size functions .
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