Seminars
- April 22, 2021 – Bridging the gap between simulations and instrument data – domain adaptation for deep learning in astronomy
- March 18, 2021 – Putting AI on a Diet: TinyML and Efficient Deep Learning
- Feb. 25, 2021 – Measuring QCD Splittings with Invertible Networks
- Feb. 3, 2021 – Domain adaptation for cross-domain studies in astronomy
- Nov. 16, 2020 – Large-Scale Field-Programmable Analog Arrays for on-chip machine learning in extreme environments
- Oct. 15, 2020 – LGN: A Lorentz Group Equivariant Neural Network for Particle Physics
- Sept. 22, 2020 – Intelliquench: Machine Learning for real-time monitoring of superconducting magnets
- May 6, 2020 – AI for Particle Physics: Better, Smarter, Faster
News
- April 30, 2021 – Scaling Inference in High Energy Particle Physics at Fermilab Using NVIDIA Triton Inference Server
- Jan. 24, 2021 – Developing Algorithms That Might One Day Be Used Against You
- Jan. 8, 2021 – Fermilab receives DOE funding to develop machine learning for particle accelerators
- Nov. 25, 2020 – Graph Convolutional Operators in the PyTorch JIT
- Sept. 24, 2020 – The next big thing: the use of graph neural networks to discover particles
- May 5, 2020 – How Self-Driving Telescopes Could Transform Astronomy
- Aug. 27, 2019 – Fermilab-led team tests Azure AI for particle physics data challenge
- Aug. 15, 2019 – A glimpse into the future: accelerated computing for accelerated particles
- Jan. 29, 2019 – Fermilab scientists help push AI to unprecedented speeds
- Artificial Intelligence Accelerates Dark Matter Search