| The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery C Lu*, C Lu*, RT Lange*, J Foerster, J Clune, D Ha arXiv preprint arXiv:2408.06292, 2024 | 71* | 2024 |
| evosax: JAX-based Evolution Strategies RT Lange Genetic and Evolutionary Computation Conference Companion (GECCO), URL http …, 2022 | 61* | 2022 |
| gymnax: A JAX-based reinforcement learning environment library RT Lange URL http://github.com/RobertTLange/gymnax, 2022 | 52 | 2022 |
| Discovering Evolution Strategies via Meta-Black-Box Optimization R Tjarko Lange, T Schaul, Y Chen, T Zahavy, V Dallibard, C Lu, S Singh, ... 11th International Conference on Learning Representations, ICLR 2023, 2023 | 47* | 2023 |
| Neural surprise in somatosensory Bayesian learning S Gijsen*, M Grundei*, RT Lange, D Ostwald, F Blankenburg PLOS Computational Biology 17 (2), e1008068, 2021 | 41 | 2021 |
| JaxMARL: Multi-Agent RL Environments and Algorithms in JAX A Rutherford, B Ellis, M Gallici, J Cook, A Lupu, G Ingvarsson, T Willi, ... Proceedings of the 23rd International Conference on Autonomous Agents and …, 2024 | 36* | 2024 |
| Discovering Attention-Based Genetic Algorithms via Meta-Black-Box Optimization RT Lange, T Schaul, Y Chen, C Lu, T Zahavy, V Dalibard, S Flennerhag Genetic and Evolutionary Computation Conference Companion (GECCO), 2023 | 31 | 2023 |
| Fish shoals resemble a stochastic excitable system driven by environmental perturbations L Gómez-Nava, RT Lange, PP Klamser, J Lukas, L Arias-Rodriguez, ... Nature Physics 19 (5), 663-669, 2023 | 27 | 2023 |
| On Lottery Tickets and Minimal Task Representations in Deep Reinforcement Learning MA Vischer*, RT Lange*, H Sprekeler 10th International Conference on Learning Representations, ICLR 2022, 2022 | 26 | 2022 |
| Large language models as evolution strategies R Lange, Y Tian, Y Tang Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2024 | 23 | 2024 |
| Discovering Temporally-Aware Reinforcement Learning Algorithms MT Jackson, C Lu, L Kirsch, RT Lange, S Whiteson, JN Foerster Second Agent Learning in Open-Endedness Workshop, 2023 | 17 | 2023 |
| Learning not to learn: Nature versus nurture in silico RT Lange, H Sprekeler AAAI Conference on Artificial Intelligence, 2022 | 14 | 2022 |
| The lottery ticket hypothesis: A survey RT Lange https://roberttlange.github.io/posts/2020/06/lottery-ticket-hypothesis/, 2020 | 10 | 2020 |
| NeuroEvoBench: Benchmarking Evolutionary Optimizers for Deep Learning Applications R Lange, Y Tang, Y Tian Advances in Neural Information Processing Systems 36, 32160-32172, 2023 | 7 | 2023 |
| MLE-Infrastructure: A Set of Lightweight Tools for Distributed Machine Learning Experimentation RT Lange URL https://github.com/mle-infrastructure, 2021 | 7 | 2021 |
| Discovering Preference Optimization Algorithms with and for Large Language Models C Lu, S Holt, C Fanconi, AJ Chan, J Foerster, M van der Schaar, ... arXiv preprint arXiv:2406.08414, 2024 | 6 | 2024 |
| Position Paper: Leveraging Foundational Models for Black-Box Optimization: Benefits, Challenges, and Future Directions X Song, Y Tian, RT Lange, C Lee, Y Tang, Y Chen arXiv preprint arXiv:2405.03547, 2024 | 6* | 2024 |
| Semantic RL with Action Grammars: Data-Efficient Learning of Hierarchical Task Abstractions RT Lange, A Faisal Deep Reinforcement Learning Workshop (NeurIPS, 2019), 2019 | 6 | 2019 |
| Evolution transformer: In-context evolutionary optimization R Lange, Y Tian, Y Tang Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2024 | 4 | 2024 |
| Reinforcement Learning with Structured Hierarchical Grammar Representations of Actions P Christodoulou*, RT Lange*, A Shafti, AA Faisal arXiv preprint arXiv:1910.02876, 2019 | 4 | 2019 |
Chris LuOpenAIVerifisert e-postadresse på openai.com
