Arthur Renard

Applied Mathematician & AI Researcher

Exploring the frontiers of AI in reasoning.

Currently working at Xent Labs as a Deep Learning Researcher. Graduate from ETH Zürich with a Master's in Applied Mathematics.

Research Projects

Exploring AI, mathematical reasoning, and symbolic regression at EPFL

Symbolic Math Solver

Symbolic Math Solver

Master's Thesis - ETH Zürich | Supervised by Clément Hongler - EPFL

PyTorchTransformersSymbolic RegressionFunctional Equations

This research explores the intersection of functional equations, symbolic regression, and deep learning through innovative methods. I developed Symbolic Math Solver (SMS), a novel framework extending ...

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Paper submission in preparation
Boolformer

Boolformer

Under review - ICML 2025 | Stéphane d'Ascoli*, Arthur Renard*, Emmanuel Abbé, Clément Hongler, Vassilis Papadopoulos, Josh Susskind, Samy Bengio - APPLE, EPFL

PyTorchTransformersAcademic ResearchSymbolic Regression

We introduce Boolformer, a Transformer-based model trained to perform end-to-end symbolic regression of Boolean functions. The model can predict compact formulas for complex functions not seen during ...

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GitHub
Under review at ICML 2025

Experience Highlight

Current research position

Deep Learning Researcher

Xent Labs

2025 - Now

Working on Xent Games — an LLM-native game space where AI agents play in LLM-defined environments with varying difficulty levels. This platform aims to develop advanced AI capabilities including reasoning, cooperation, and critical thinking.

Key Publications & Projects

Boolformer: End-to-end symbolic regression for Boolean functions

Phase Transition Finder: Published at GECCO 2024, doubling discovery rate in Lenia

Symbolic Math Solver: International Mathematical Olympiad problems solver powered by AI

LLM Security: Exploring optimization methods in embedding space for enhanced inference

Core Skills

Technical expertise and professional competencies

Programming

  • Python/PyTorch
  • C++
  • Rust
  • Next.js/React Native

Machine Learning

  • Deep Learning
  • Transformers
  • Symbolic Regression
  • LLMs and their applications

Languages

  • French (Native)
  • English (C1, Cambridge)
  • German (Intermediate)
  • Dutch (Basic)

Get In Touch

Feel free to reach out for collaborations or just a friendly chat

LinkedIn ProfileGitHub Profile
Lausanne, Switzerland