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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
About me
About me
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Posts
Introspection on a decade of coding
Published:
Autobiography of a nerd
Ma thèse en 180 secondes
Published:
En 2022 j’ai eu la chance de participer au concours Ma thèse en 180 secondes, un concours de vulgarisation de thèses en 3 minutes. Retrouvez ici la vidéo de mon passage en finale régionale et mon script.
Developing a chatbot
Published:
I developed a Twitch chatbot.
Explaining GENE
Published:
A Geometric Encoding for Neural Networks Evolution
My tech stack
Published:
After a few years of testing and tweaking, I decided to make a blog about my tech stack.
portfolio
Multidimensional GP for multiclass classification
Published:
Jupyter notebook implementing, presenting and explaining a research paper for Data Science specialization.
Genepy
Published:
Artificial life simulation in a 2D environment, with a custom implementation of NEAT for the brains.
NeuroEvolution.jl
Published:
A Julia implementation of NEAT-based neuroevolution algorithms (NEAT, CPPN, HyperNEAT)
Groinkbot
Published:
Multi-platform chatbot framework, based on a modular architecture and with a high-level interface.
GENE
Published:
A Geometric Encoding for Neural Network Evolution
publications
Security of instant messaging applications (FR)
Authors: Wajih Jmaiel, Paul Templier
Published in RiskInsight blog (Wavestone), 2019
Detecting security incidents with Machine Learning (FR)
Authors: Hugo Moret, Paul Templier
Published in RiskInsight blog (Wavestone), 2019
Evolving a Dota 2 bot: Illuminating search in CGP and NEAT
Authors: Paul Templier, Lucas Hervier, Dennis G. Wilson
Published in Competition at GECCO 2020, 2020
In this work we present an evolution-based approach applied to Dota 2 in the Project Breezy challenge. The goal of this project is to train an agent to play a 1v1 Midlane match against the game's bots of varrying difficulties, with both sides playing Shadow Fiend. The approach we implemented relies on the MAP-elites algorithm assisted with a neural-based simulator of the game to increase behavior diversity and reduce computation load, using CGP agents or NEAT networks as individuals.
A Geometric Encoding for Neural Network Evolution
Authors: Paul Templier, Emmanuel Rachelson, Dennis G. Wilson
Published in GECCO 2021 (Genetic and Evolutionary Computation Conference), 2021
A major limitation to the optimization of artificial neural networks (ANN) with evolutionary methods lies in the high dimensionality of the search space, the number of weights growing quadratically with the size of the network. This leads to expensive training costs, especially in evolution strategies which rely on matrices whose sizes grow with the number of genes. We introduce a geometric encoding for neural network evolution (GENE) as a representation of ANN parameters in a smaller space that scales linearly with the number of neurons, allowing for efficient parameter search. Each neuron of the network is encoded as a point in a latent space and the weight of a connection between two neurons is computed as the distance between them. The coordinates of all neurons are then optimized with evolution strategies in a reduced search space while not limiting network fitness and possibly improving search.
talks
Talk 1 on Relevant Topic in Your Field
Published:
This is a description of your talk, which is a markdown files that can be all markdown-ified like any other post. Yay markdown!
Conference Proceeding talk 3 on Relevant Topic in Your Field
Published:
This is a description of your conference proceedings talk, note the different field in type. You can put anything in this field.
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
This is a description of a teaching experience. You can use markdown like any other post.
Teaching experience 2
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.