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Image for Learning as Solving the Right PDE: Geometry, separability, curved manifolds and the structure hiding inside every learning problem

Learning as Solving the Right PDE: Geometry, separability, curved manifolds and the structure hiding inside every learning problem

By: Alexandre Quemy

What if supervised learning were just solving the right partial differential equation? This talk traces the research journey behind Intrinsic Green's Learning — from a 2D Poisson classifier to Riemannian manifolds, brain-computer interfaces, and open problems at the frontier of geometry and machine learning.

Elements Scientific Conference

2026-10-23

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Latest Insight

Image for Function Calling in LLMs: A Signature Model Approach

Function Calling in LLMs: A Signature Model Approach

By: Alexandre Quemy

A client-side solution for LLM function calling using Python's Pydantic and function signatures to enable more flexible, context-aware function calling.

quemy.info

2025-06-12

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Featured Book

Cover for Introduction à l'informatique quantique

Introduction à l'informatique quantique

Gregoire Cattan

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All Talks & Presentations

Learning as Solving the Right PDE: Geometry, separability, curved manifolds and the structure hiding inside every learning problem

Presented by Alexandre Quemy

What if supervised learning were just solving the right partial differential equation? This talk traces the research journey behind Intrinsic Green's Learning — from a 2D Poisson classifier to Riemannian manifolds, brain-computer interfaces, and open problems at the frontier of geometry and machine learning.

Elements Scientific Conference

2026-10-23

Event Details →

Proofs: pivoting an agentic pre-seed startup

Presented by Alexandre Quemy

At Proofs, we operated a major shift from an autonomous multi-agents platform for end-to-end software development to human-in-the-loop multi-agents terminal-based tooling for software architecture.
We discuss a two years trajectory, from product market fit to technical and conceptual issues with agentic platforms.

AI SUMMIT BARCELONA

2026-09-15

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LLM Function Calling: a Signature Model Approach

Presented by Alexandre Quemy

I present a client-side alternative to native function calling with many benefits in terms of cost, agentic capabilities and scalability.

Data Science Summit 2025 AI // ML Edition

2025-06-05

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All Articles & Insights

Function Calling in LLMs: A Signature Model Approach

By: Alexandre Quemy

quemy.info - 2025-06-12

Introduces a novel approach to function calling in Large Language Models using a 'Signature Model' method. Proposes a client-side solution that overcomes current limitations in function calling.

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Stop using 'Correlation is not causation' and maybe stop using correlation

By: Alexandre Quemy

quemy.info - 2021-02-03

A critical examination of the concept of correlation, challenging the oversimplified "correlation is not causation" mantra and exploring the mathematical limitations of correlation coefficients.

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On controlling the propagation of numerical errors

By: Alexandre Quemy

quemy.info - 2021-01-05

Explores the challenges of numerical computations and floating-point arithmetic, focusing on how rounding errors propagate during calculations using the CESTAC method.

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Distributions, Laplace Transform and Initial Value Problem

By: Alexandre Quemy

quemy.info - 2021-01-09

Explores solving Initial Value Problems using distributions and the Laplace transform, presenting a unique algebraic perspective on the Laplace transform.

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Formal Publications

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Showing 31 of 31 publications

2026

0 publications

Intrinsic Green's Learning: Supervised Learning on Manifolds via Inverse PDE

Quemy, A. (2026) • ICLR 2026 @ AI & PDE Workshop
AI & Machine Learning

2025

0 publications

Parkinson disease classification: a comparison of quantum and RBF kernels using support vector machine

Cattan, G., Olmos, J., Chauhan, Y., Martínez, F. (2025) • Quantum Machine Intelligence 7 (1), 64
Quantum Computing AI & Machine Learning

The Riemannian Means Field Classifier for EEG-Based BCI Data

Andreev, A., Cattan, G., Congedo, M. (2025) • Sensors 25 (7), 2305
Brain-Computer Interfaces AI & Machine Learning

2024

0 publications

Evaluation of the Electroencephalogram Conformer for the P300 Signal

Aristimunha, B., Cattan, G., Andreev, A. (2024) • Technical Report
Brain-Computer Interfaces AI & Machine Learning

Art makes quantum intuitive

Cattan, G., Duś, K., Kusmia, S., Stopa, T. (2024) • Frontiers in Quantum Science and Technology 3, 1397130
Quantum Computing

Quantum Denoising in the Realm of Brain-Computer Interfaces: A Preliminary Study

Mostafa, A., Chauhan, Y., Ahmed, W., Cattan, G. (2024) • October 6 University, Egypt; National Institute of Science Education
Quantum Computing Brain-Computer Interfaces

Quantum machine-based decision support system for the detection of schizophrenia from EEG records

Aksoy, G., Cattan, G., Chakraborty, S., Karabatak, M. (2024) • Journal of Medical Systems 48 (1), 29
Quantum Computing AI & Machine Learning Brain-Computer Interfaces

2023

0 publications

A large reproducible benchmark on text classification for the legal domain based on the ECHR-OD repository

Quemy, A., Wrembel, R., Łopuszyńska, N., Papadakis, G., Delgado, A.D. (2023) • Information Systems 119, 102258
Natural Language Processing AI & Machine Learning Data Science

Judicial Independence and Impartiality: Tenure Changes at the European Court of Human Rights

Molbæk-Steensig, H., Quemy, A. (2023) • European Journal of International Law 34 (3), 581-614
AI & Machine Learning Data Science

MultiZenoTravel: a Tunable Benchmark for Multi-Objective Planning with Known Pareto Front

Quemy, A., Schoenauer, M., Dreo, J. (2023) • arXiv preprint arXiv:2304.14659
AI & Machine Learning

Case-Based and Quantum Classification for ERP-Based Brain–Computer Interfaces

Cattan, G.H., Quemy, A. (2023) • Brain Sciences 13 (2), 303
Quantum Computing AI & Machine Learning Brain-Computer Interfaces

First steps towards quantum machine learning applied to the classification of event-related potentials

Cattan, G., Quemy, A., Andreev, A. (2023) • arXiv preprint arXiv:2302.02648
Quantum Computing AI & Machine Learning Brain-Computer Interfaces

Artificial intelligence and fair trial rights

Molbæk-Steensig, H., Quemy, A. (2023) • Oxford University Press
AI & Machine Learning

ydata-profiling: Accelerating data-centric AI with high-quality data

Clemente, F., Ribeiro, G.M., Quemy, A., Santos, M.S., Pereira, R.C., Barros, A. (2023) • Neurocomputing 554, 126585
Data Science Software Engineering

Towards an architectural framework for intelligent virtual agents using probabilistic programming

Andreev, A., Cattan, G. (2023) • arXiv preprint arXiv:2307.10693
AI & Machine Learning Software Engineering

pyRiemann-qiskit: a sandbox for quantum classification experiments with riemannian geometry

Andreev, A., Cattan, G., Chevallier, S., Barthélemy, Q. (2023) • Research Ideas and Outcomes 9, e101006
Quantum Computing AI & Machine Learning Software Engineering

2021

0 publications

Cautiously Making Friends with AI: Machine Learning for human rights research and practice

Molbæk-Steensig, H., Quemy, A. (2021) • AI & Human Rights Friend or Foe?, The Erasmus School of Law
AI & Machine Learning Data Science

Paradiseo: From a Modular Framework for Evolutionary Computation to the Automated Design of Metaheuristics

Dreo, J., Liefooghe, A., Verel, S., Schoenauer, M., Merelo, J., Quemy, A., Bouvier, B., Gmys, J. (2021) • Genetic and Evolutionary Computation Conference (GECCO)
Featured
AI & Machine Learning Software Engineering

ECHR-OD: On Building an Integrated Open Repository of Legal Documents for Machine Learning Applications

Quemy, A., Wrembel, R. (2021) • Information Systems
Natural Language Processing Data Science

2020

0 publications

GBEx, towards Graph-Based Explanations

Mróz, P., Quemy, A., et al. (2020) • International Conference Tools with Artificial Intelligence (ICTAI)
AI & Machine Learning Data Science

On Integrating and Classifying Legal Text Documents

Quemy, A., Wrembel, R. (2020) • International Conference on Database and Expert Systems Applications (DEXA)
Natural Language Processing Data Science

Two-stage Optimization for Machine Learning Workflow

Quemy, A. (2020) • Information Systems
AI & Machine Learning Data Science

2019

0 publications

Binary Classification In Unstructured Space With Hypergraph Case-Based Reasoning

Quemy, A. (2019) • Information Systems
AI & Machine Learning Data Science

Data Pipeline Selection and Optimization

Quemy, A. (2019) • International Workshop on Design, Optimization, Languages and Analytical Processing of Big Data (DOLAP)
Data Science Software Engineering

Binary Classification With Hypergraph Case-Based Reasoning

Quemy, A. (2019) • International Workshop on Design, Optimization, Languages and Analytical Processing of Big Data (DOLAP)
AI & Machine Learning Data Science

2018

0 publications

Binary Classification With Hypergraph Case-Based Reasoning

Quemy, A. (2018) • International Workshop on Design, Optimization, Languages and Analytical Processing of Big Data (DOLAP) @ EDBT/ICDT Joint Conference
AI & Machine Learning Data Science

AI for the legal domain: an explainability challenge

Quemy, A. (2018) • PhD Student Research Competition, IFIP World Computer Congress
AI & Machine Learning Natural Language Processing

Unsupervised Video Semantic Partitioning Using IBM Watson and Topic Modelling

Quemy, A., Jamrog, K., Janiszewski, M. (2018) • International Workshop on Data Analytics solutions for Real-LIfe APplications (DARLI-AP) @ EDBT/ICDT Joint Conference
AI & Machine Learning Data Science

2017

0 publications

Data Science Techniques for Law and Justice: Current State of Research and Open Problems

Quemy, A. (2017) • Advances in Databases and Information Systems (ADBIS) Workshops and Short papers
Data Science AI & Machine Learning

2015

0 publications

Solving Large MultiZenoTravel Benchmarks with Divide-and-Evolve

Quemy, A., Schoenauer, M., Vidal, V., Dréo, J., Savéant, P. (2015) • Learning and Intelligent Optimization (LION)
AI & Machine Learning

True Pareto Fronts for Multi-objective AI Planning Instances

Quemy, A., Schoenauer, M. (2015) • Evolutionary Computation in Combinatorial Optimization (EvoCOP)
AI & Machine Learning