Hi, I'm Timon.

Intro

Currently I am a PhD student with Prof. Foerster J. at FLAIR at the University of Oxford and previously Vector Institute, University of Toronto. During my PhD, I was a Research Intern at Google DeepMind in the Montreal team. Before my PhD, I was a Research Scientist at Nnaisense, where we developed Deep Learning based technologies to solve problems in industry. Before joining Nnaisense, I completed my MSc in Artificial Intelligence at the Università della Svizzera italiana.

My research interests include Multi-Agent Reinforcement Learning, Generative Models and Meta-Learning.

Highlighted Work

No Regrets: Investigating and Improving Regret Approximations for Curriculum Discovery, Arxiv
Rutherford A., Beukman M., Willi T., Lacerda B., Hawes N., Foerster J.

Jafar: An Open-Source Genie Reimplemention in Jax, Workshop @ ICML 2024
Willi* T., Jackson* Matthew T.,, Foerster J.

Mixture of Experts in a Mixture of RL settings, RLC 2024
Willi* T., Obando-Ceron* J., Foerster J.,Dziugaite K., Castro P.

Mixtures of Experts Unlock Parameter Scaling for Deep RL, ICML 2024 (spotlight, 3.5%)
Obando-Ceron* J., Sokar* G., Willi* T., Lyle C., Farebrother J., Foerster J., Dziugaite K., Precup D., Castro P.

JaxMARL: Multi-Agent RL Environments and Algorithms in JAX, AAMAS 2024, (ext. abs)
Rutherford* A., Ellis* B., Gallici* M., Cook* J., Lupu* A., Ingvarsson* G., Willi* T., Khan A., Schroeder de Witt C., Souly A., Bandyopadhyay S., Samvelyan M, Jiang M., Lange R., Whiteson S., Lacerda B., Hawes N., Rocktäschel T., Lu* C., Foerster J.

Analysing the Sample Complexity of Opponent Shaping, AAMAS 2024 (oral)
Fung K., Zhang Q., Lu C., Willi T., Foerster J.

Leading the Pack: N-player Opponent Shaping, Workshop @ Neurips 2023 (oral)
Souly A.,Willi T.,Khan A., Kirk R., Lu C., Grefenstette E., Rocktäschel T.

Pax: Scalable Opponent Shaping in Jax, Github
Willi T., Khan* A., Kwan* N., Lu C., Foerster J.

Scaling Opponent Shaping to High Dimensional Games, AAMAS 2024 (oral)
Khan* A., Willi* T., Kwan* N.,Tacchetti A.,Lu C., Grefenstette E., Rocktäschel T., Foerster J.

Adversarial Cheap Talk, ICML 2023 & 5 Workshops @ ICML 2022
Lu C., Willi T., Letcher A., Foerster J.

Model-Free Opponent Shaping, ICML 2022 (short presentation, 22%)
Lu C., Willi T., Schroeder de Witt C., Foerster J.

COLA: Consistent Learning with Opponent-Learning Awareness, ICML 2022 (short presentation, 22%)
Willi T.*, Treutlein J.*, Letcher A.*, Foerster J.

Recurrent Neural Processes, Neurips 2019 BDL Workshop (oral)
Willi T., Masci J., Schmidhuber J., Osendorfer C.

Master's Thesis "Recurrent Neural Processes"
Supervised by Schmidhuber J. and Osendorfer C.

Miscellaneous

Talks

• Google Deepmind - Dec 9, 2022: Opponent Shaping

Races

Contact

• GitHub
• LinkedIn
• X

Elements

i = 0;

while (!deck.isInOrder()) {
    print 'Iteration ' + i;
    deck.shuffle();
    i++;
}

print 'It took ' + i + ' iterations to sort the deck.';