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Hugo Caselles-Dupré.

Research Director at Obvious Research, in partnership with ISIR (Sorbonne University). I'm also an artist of Obvious, a collective interested in Art & Machine Learning. You can learn more about us here. Currently leading Obvious Research, a research laboratory on Generative AI (image, video, sound) in partnership with ISIR (Sorbonne University). We have an ANR grant of over 1M€ to invent new AI algorithms for artistic creation (2023-2027). We are hiring interns, postdocs, research engineers and PhDs, contact me!

In 2021-2023, I did a Post-Doc at ISIR (Sorbonne University) under the supervision of Olivier Sigaud and Mohamed Chetouani, studying the teachability of autonomous agents. In 2021, I graduated with a PhD from the Flowers Laboratory of ENSTA ParisTech and INRIA (supervised by David Filliat and Michaël Garcia-Ortiz). The title of my thesis is "On the Role of Action and Machine Learning in Artificial Agent Perception".

Hugo Caselles-Dupré's Projects

deep_q-network icon deep_q-network

Implementation of DeepMind's Deep Q-Network for Reinforcement Learning on OpenAI Gym, using Python with Keras.

entropic_affinities icon entropic_affinities

A sparsification method for graph-based clustering and semi-supervised learning tasks, implemented on Python.

neurips19-sbdrl icon neurips19-sbdrl

Code for NeurIPS 2019 paper: "Symmetry-Based Disentangled Representation Learning requires Interaction with Environments" by H. Caselles-Dupré, M. Garcia-Ortiz and D. Filliat.

paper_notes icon paper_notes

Paper notes for my PhD on Machine Learning (mostly focused on Reinforcement Learning)

s-vs-d icon s-vs-d

Research on autotelic teachable agents with demonstrations.

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