| Brain-inspired learning in artificial neural networks: a review S Schmidgall, R Ziaei, J Achterberg, L Kirsch, S Hajiseyedrazi, ... APL Machine Learning 2 (2), 2024 | 27 | 2024 |
| NeuroBench: A Framework for Benchmarking Neuromorphic Computing Algorithms and Systems J Yik, KV Berghe, D Blanken, Y Bouhadjar, M Fabre, P Hueber, D Kleyko, ... arXiv preprint arXiv:2304.04640, 2023 | 15* | 2023 |
| SpikePropamine: Differentiable Plasticity in Spiking Neural Networks S Schmidgall, J Ashkanazy, W Lawson, J Hays Frontiers in Neurorobotics, 2021 | 8 | 2021 |
| Meta-SpikePropamine: Learning to learn with synaptic plasticity in spiking neural networks S Schmidgall, J Hays Frontiers in Neuroscience 17, 671, 2023 | 7* | 2023 |
| Adaptive Reinforcement Learning through Evolving Self-Modifying Neural Networks S Schmidgall Proceedings of the 2020 Genetic and Evolutionary Computation Conference …, 2020 | 7 | 2020 |
| Addressing cognitive bias in medical language models S Schmidgall, C Harris, I Essien, D Olshvang, T Rahman, JW Kim, R Ziaei, ... arXiv preprint arXiv:2402.08113, 2024 | 6 | 2024 |
| Surgical Gym: A high-performance GPU-based platform for reinforcement learning with surgical robots S Schmidgall, A Krieger, J Eshraghian 2024 IEEE International Conference on Robotics and Automation (ICRA), 2023 | 6 | 2023 |
| AgentClinic: a multimodal agent benchmark to evaluate AI in simulated clinical environments S Schmidgall, R Ziaei, C Harris, E Reis, J Jopling, M Moor arXiv preprint arXiv:2405.07960, 2024 | 5 | 2024 |
| Language models are susceptible to incorrect patient self-diagnosis in medical applications R Ziaei, S Schmidgall NeurIPS 2023 Deep Generative Models for Healthcare Workshop, 2023, 2023 | 5 | 2023 |
| Stable Lifelong Learning: Spiking neurons as a solution to instability in plastic neural networks S Schmidgall, J Hays Proceedings of the 2022 Neuro-Inspired Computing Elements Conference, 2021 | 5 | 2021 |
| Synaptic motor adaptation: A three-factor learning rule for adaptive robotic control in spiking neural networks S Schmidgall, J Hays Proceedings of the 2023 International Conference on Neuromorphic Systems, 2023 | 3 | 2023 |
| Biological connectomes as a representation for the architecture of artificial neural networks S Schmidgall, C Schuman, M Parsa Proceedings of the 2023 AAAI Conference on Artificial Intelligence "Systems …, 2023 | 3 | 2023 |
| General-purpose foundation models for increased autonomy in robot-assisted surgery S Schmidgall, JW Kim, A Kuntz, AE Ghazi, A Krieger arXiv preprint arXiv:2401.00678, 2024 | 2 | 2024 |
| Evolutionary self-replication as a mechanism for producing artificial intelligence S Schmidgall, J Hays arXiv preprint arXiv:2109.08057, 2021 | 1 | 2021 |
| Optimal Localized Trajectory Planning of Multiple Non-holonomic Vehicles A Lukyanenko, H Camphire, A Austin, S Schmidgall, D Soudbakhsh 2021 IEEE Conference on Control Technology and Applications (CCTA), 820-825, 2021 | 1 | 2021 |
| Self-Constructing Neural Networks through Random Mutation S Schmidgall ICLR 2021 Never-Ending Reinforcement Learning Workshop, 2021 | 1 | 2021 |
| Surgical Robot Transformer (SRT): Imitation Learning for Surgical Tasks JW Kim, TZ Zhao, S Schmidgall, A Deguet, M Kobilarov, C Finn, A Krieger arXiv preprint arXiv:2407.12998, 2024 | | 2024 |
| Robots learning to imitate surgeons—challenges and possibilities S Schmidgall, JW Kim, A Krieger Nature Reviews Urology, 1-2, 2024 | | 2024 |
| General surgery vision transformer: A video pre-trained foundation model for general surgery S Schmidgall, JW Kim, J Jopling, A Krieger arXiv preprint arXiv:2403.05949, 2024 | | 2024 |
| Locked fronts in a discrete time discrete space population model M Holzer, Z Richey, W Rush, S Schmidgall Journal of mathematical biology 85 (4), 39, 2022 | | 2022 |
Rojin ZiaeiResearch Assistant Stanford在 stanford.edu 的电子邮件经过验证
