Jan Finkbeiner - JoVE Visualize

Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Policies

Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Policies

Filters

Jan Finkbeiner

Showing results (1-10 of 3) with videos related to

Pageof 1

Sort By:

Physical Review Letters|May 3, 2024

Generating Minimal Training Sets for Machine Learned PotentialsJan Finkbeiner, Samuel Tovey, Christian Holm

Nature Computational Science|September 16, 2025

Neuromorphic principles in self-attention hardware for efficient transformersNathan Leroux, Jan Finkbeiner, Emre Neftci

Nature Computational Science|September 8, 2025

Analog in-memory computing attention mechanism for fast and energy-efficient large language modelsNathan Leroux, Paul-Philipp Manea, Chirag Sudarshan, et al.

Pageof 1

Search research articles

Showing results (1-10 of 3) with videos related to

Sort By:

Pageof 1

Physical Review Letters|May 3, 2024

Generating Minimal Training Sets for Machine Learned PotentialsJan Finkbeiner, Samuel Tovey, Christian Holm

Nature Computational Science|September 16, 2025

Neuromorphic principles in self-attention hardware for efficient transformersNathan Leroux, Jan Finkbeiner, Emre Neftci

Nature Computational Science|September 8, 2025

Analog in-memory computing attention mechanism for fast and energy-efficient large language modelsNathan Leroux, Paul-Philipp Manea, Chirag Sudarshan, et al.

Pageof 1