Implicitly defined, continuous, differentiable signal representations parameterized by neural
networks have emerged as a powerful paradigm, offering many possible benefits over …

Neural representations have emerged as a new paradigm for applications in rendering,
imaging, geometric modeling, and simulation. Compared to traditional representations such as …

Numerical integration is a foundational technique in scientific computing and is at the core
of many computer vision applications. Among these applications, neural volume rendering …

Camera sensors rely on global or rolling shutter functions to expose an image. This fixed
function approach severely limits the sensors' ability to capture high-dynamic-range (HDR) …

The cameras in modern gaze-tracking systems suffer from fundamental bandwidth and power
limitations, constraining data acquisition speed to 300 Hz realistically. This obstructs the …

Cryo-electron microscopy (cryo-EM) is an imaging modality that provides unique insights
into the dynamics of proteins and other building blocks of life. The algorithmic challenge of …

Cryo-electron microscopy (cryo-EM) has become a tool of fundamental importance in
structural biology, helping us understand the basic building blocks of life. The algorithmic …

There has been a rapidly growing interest in Automatic Symptom Detection (ASD) and
Automatic Diagnosis (AD) systems in the machine learning research literature, aiming to assist …

Compressive imaging using coded apertures (CA) is a powerful technique that can be used
to recover depth, light fields, hyperspectral images and other quantities from a single …

With recent advances in high-throughput Electron Microscopy (EM) imaging it is now possible
to image an entire nervous system of organisms like Drosophila melanogaster. One of the …