Sam Greydanus

According to our database, Sam Greydanus authored at least 12 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Scaling Down Deep Learning with MNIST-1D.

Samuel Greydanus, Dmitry Kobak

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Nature's Cost Function: Simulating Physics by Minimizing the Action.

Tim Strang, Isabella Caruso, Sam Greydanus

CoRR, 2023

2022

A Tutorial on Structural Optimization.

Sam Greydanus

CoRR, 2022

Dissipative Hamiltonian Neural Networks: Learning Dissipative and Conservative Dynamics Separately.

Andrew Sosanya, Sam Greydanus

CoRR, 2022

2021

Piecewise-constant Neural ODEs.

Sam Greydanus, Stefan Lee, Alan Fern

CoRR, 2021

2020

Scaling *down* Deep Learning.

Sam Greydanus

CoRR, 2020

Lagrangian Neural Networks.

Miles D. Cranmer, Sam Greydanus, Stephan Hoyer, Peter W. Battaglia, David N. Spergel, Shirley Ho

CoRR, 2020

2019

Neural reparameterization improves structural optimization.

Stephan Hoyer, Jascha Sohl-Dickstein, Sam Greydanus

CoRR, 2019

Hamiltonian Neural Networks.

Samuel Greydanus, Misko Dzamba, Jason Yosinski

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Learning Finite State Representations of Recurrent Policy Networks.

Anurag Koul, Alan Fern, Sam Greydanus

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

Visualizing and Understanding Atari Agents.

Samuel Greydanus, Anurag Koul, Jonathan Dodge, Alan Fern

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

Learning the Enigma with Recurrent Neural Networks.

Sam Greydanus

CoRR, 2017