Brandon Amos

Research Scientist

I am a Research Scientist at Facebook AI (FAIR) and study machine learning and optimization. I completed a PhD with Prof. Zico Kolter at CMU on optimization-based modeling components for learning and control.


Machine learning, optimization, control, reinforcement learning, meta-learning, structured prediction, and energy-based modeling

Latest Publications

ICLR - May 3, 2021

Neural Spatio-Temporal Point Processes

Ricky T. Q. Chen, Brandon Amos, Maximilian Nickel

ICLR - March 3, 2021

Learning Neural Event Functions for Ordinary Differential Equations

Ricky T. Q. Chen, Brandon Amos, Maximilian Nickel

Learning Meets Combinatorial Optimization Workshop at NeurIPS - December 12, 2020

Fit The Right NP-Hard Problem: End-to-end Learning of Integer Programming Constraints

Anselm Paulus, Michal Rolinek, Vit Musil, Brandon Amos, Georg Martius

Differential Geometry for ML Workshop at NeurIPS - December 11, 2020

Deep Riemannian Manifold Learning

Aaron Lou, Maximilian Nickel, Brandon Amos

ICML - July 12, 2020

The Differentiable Cross-Entropy Method

Brandon Amos, Denis Yarats

Learning for Dynamics & Control (L4DC) - June 10, 2020

Objective Mismatch in Model-based Reinforcement Learning

Nathan Lambert, Brandon Amos, Omry Yadan, Roberto Calandra

NeurIPS - December 8, 2019

Differentiable Convex Optimization Layers

Akshay Agrawal, Brandon Amos, Shane Barratt, Stephen Boyd, Steven Diamond, J. Zico Kolter