We propose to apply several gradient estimation techniques to enable the...
Estimating uncertainty is at the core of performing scientific measureme...
Recurrent neural networks have been shown to be effective architectures ...
We present a light field imaging system that captures multiple views of ...
Many physical systems can be best understood as sets of discrete data wi...
The computational cost for high energy physics detector simulation in fu...
MadJax is a tool for generating and evaluating differentiable matrix ele...
Cryogenic electron microscopy (cryo-EM) provides images from different c...
Image-based jet analysis is built upon the jet image representation of j...
We revisit empirical Bayes in the absence of a tractable likelihood func...
We propose a novel method for gradient-based optimization of black-box
s...
We introduce Continual Learning via Neural Pruning (CLNP), a new method ...
Machine learning is an important research area in particle physics, begi...
Several techniques for domain adaptation have been proposed to account f...
Building on the notion of a particle physics detector as a camera and th...