Robert T. Lange

Orcid: 0009-0005-8799-1138

Affiliations:
  • Sakana.AI, Tokyo, Japan
  • Technical University of Berlin, Germany


According to our database1, Robert T. Lange authored at least 22 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

Online presence:

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Bibliography

2024
Stein Variational Evolution Strategies.
CoRR, 2024

The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery.
CoRR, 2024

NAVIX: Scaling MiniGrid Environments with JAX.
CoRR, 2024

Discovering Minimal Reinforcement Learning Environments.
CoRR, 2024

Discovering Preference Optimization Algorithms with and for Large Language Models.
CoRR, 2024

Position: Leverage Foundational Models for Black-Box Optimization.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Behaviour Distillation.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Discovering Temporally-Aware Reinforcement Learning Algorithms.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Large Language Models As Evolution Strategies.
Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2024

Evolution Transformer: In-Context Evolutionary Optimization.
Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2024


2023
JaxMARL: Multi-Agent RL Environments in JAX.
CoRR, 2023

NeuroEvoBench: Benchmarking Evolutionary Optimizers for Deep Learning Applications.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Lottery Tickets in Evolutionary Optimization: On Sparse Backpropagation-Free Trainability.
Proceedings of the International Conference on Machine Learning, 2023

Discovering Evolution Strategies via Meta-Black-Box Optimization.
Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023

Discovering Attention-Based Genetic Algorithms via Meta-Black-Box Optimization.
Proceedings of the Genetic and Evolutionary Computation Conference, 2023

evosax: JAX-Based Evolution Strategies.
Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023

2022
On Lottery Tickets and Minimal Task Representations in Deep Reinforcement Learning.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Learning Not to Learn: Nature versus Nurture In Silico.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Neural surprise in somatosensory Bayesian learning.
PLoS Comput. Biol., 2021

2019
Reinforcement Learning with Structured Hierarchical Grammar Representations of Actions.
CoRR, 2019

Action Grammars: A Cognitive Model for Learning Temporal Abstractions.
CoRR, 2019


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