Samuel Schmidgall

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 24

Top Topics

Robotic Control

Biologically Plausible

Top Venues

Frontiers Neurorobotics

Publications

Samuel Schmidgall, Axel Krieger, Jason Eshraghian
Surgical Gym: A high-performance GPU-based platform for reinforcement learning with surgical robots. ICRA (2024)
Samuel Schmidgall, Carl Harris, Ime Essien, Daniel Olshvang, Tawsifur Rahman, Ji Woong Kim, Rojin Ziaei, Jason Eshraghian, Peter Abadir, Rama Chellappa
Addressing cognitive bias in medical language models. CoRR (2024)
Samuel Schmidgall, Ji Woong Kim, Alan Kuntz, Ahmed Ezzat Ghazi, Axel Krieger
General-purpose foundation models for increased autonomy in robot-assisted surgery. CoRR (2024)
Samuel Schmidgall, Rojin Ziaei, Carl Harris, Eduardo Pontes Reis, Jeffrey Jopling, Michael Moor
AgentClinic: a multimodal agent benchmark to evaluate AI in simulated clinical environments. CoRR (2024)
Samuel Schmidgall, Joseph Cho, Cyril Zakka, William Hiesinger
GP-VLS: A general-purpose vision language model for surgery. CoRR (2024)
Samuel Schmidgall, Ji Woong Kim, Jeffrey Jopling, Axel Krieger
General surgery vision transformer: A video pre-trained foundation model for general surgery. CoRR (2024)
Ji Woong Kim, Tony Z. Zhao, Samuel Schmidgall, Anton Deguet, Marin Kobilarov, Chelsea Finn, Axel Krieger
Surgical Robot Transformer (SRT): Imitation Learning for Surgical Tasks. CoRR (2024)
Rojin Ziaei, Samuel Schmidgall
Language models are susceptible to incorrect patient self-diagnosis in medical applications. CoRR (2023)
Samuel Schmidgall, Joe Hays
Synaptic motor adaptation: A three-factor learning rule for adaptive robotic control in spiking neural networks. ICONS (2023)
Samuel Schmidgall, Joe Hays
Synaptic motor adaptation: A three-factor learning rule for adaptive robotic control in spiking neural networks. CoRR (2023)
Samuel Schmidgall, Axel Krieger, Jason Eshraghian
Surgical Gym: A high-performance GPU-based platform for reinforcement learning with surgical robots. CoRR (2023)
Samuel Schmidgall, Jascha Achterberg, Thomas Miconi, Louis Kirsch, Rojin Ziaei, S. Pardis Hajiseyedrazi, Jason Eshraghian
Brain-inspired learning in artificial neural networks: a review. CoRR (2023)
Samuel Schmidgall, Joe Hays
Learning to learn online with neuromodulated synaptic plasticity in spiking neural networks. CoRR (2022)
Samuel Schmidgall, Catherine D. Schuman, Maryam Parsa
Biological connectomes as a representation for the architecture of artificial neural networks. CoRR (2022)
Samuel Schmidgall, Joe Hays
Stable Lifelong Learning: Spiking neurons as a solution to instability in plastic neural networks. NICE (2022)
Samuel Schmidgall, Joseph Hays
Evolutionary Self-Replication as a Mechanism for Producing Artificial Intelligence. CoRR (2021)
Samuel Schmidgall, Julia Ashkanazy, Wallace Lawson, Joe Hays
SpikePropamine: Differentiable Plasticity in Spiking Neural Networks. CoRR (2021)
Anton Lukyanenko, Heath Camphire, Avery Austin, Samuel Schmidgall, Damoon Soudbakhsh
Optimal Localized Trajectory Planning of Multiple Non-holonomic Vehicles. CCTA (2021)
Samuel Schmidgall
Self-Constructing Neural Networks Through Random Mutation. CoRR (2021)
Samuel Schmidgall
Self-Replicating Neural Programs. CoRR (2021)
Samuel Schmidgall, Julia Ashkanazy, Wallace Lawson, Joe Hays
SpikePropamine: Differentiable Plasticity in Spiking Neural Networks. Frontiers Neurorobotics 15 (2021)
Samuel Schmidgall, Joe Hays
Stable Lifelong Learning: Spiking neurons as a solution to instability in plastic neural networks. CoRR (2021)
Samuel Schmidgall
Adaptive reinforcement learning through evolving self-modifying neural networks. GECCO Companion (2020)
Samuel Schmidgall
Adaptive Reinforcement Learning through Evolving Self-Modifying Neural Networks. CoRR (2020)