59 citations · 117 across the 10 of their papers we have counts for
10 papers
Constrained Neural Networks for Interpretable Heuristic Creation to Optimise Computer Algebra Systems
Dorian Florescu, Matthew England
We present a new methodology for utilising machine learning technology in symbolic computation research. We explain how a well known human-designed heuristic to make the choice of…
Unlimited Sampling of Bandpass Signals: Computational Demodulation via Undersampling
Gal Shtendel, Dorian Florescu, Ayush Bhandari
Bandpass signals are an important sub-class of bandlimited signals that naturally arise in a number of application areas but their high-frequency content poses an acquisition chall…
Multi-Dimensional Unlimited Sampling and Robust Reconstruction
Dorian Florescu, Ayush Bhandari
In this paper we introduce a new sampling and reconstruction approach for multi-dimensional analog signals. Building on top of the Unlimited Sensing Framework (USF), we present a n…
Time Encoding via Unlimited Sampling: Theory, Algorithms and Hardware Validation
Dorian Florescu, Ayush Bhandari
An alternative to conventional uniform sampling is that of time encoding, which converts continuous-time signals into streams of trigger times. This gives rise to Event-Driven Samp…
The Surprising Benefits of Hysteresis in Unlimited Sampling: Theory, Algorithms and Experiments
Dorian Florescu, Felix Krahmer, Ayush Bhandari
The Unlimited Sensing Framework (USF) was recently introduced to overcome the sensor saturation bottleneck in conventional digital acquisition systems. At its core, the USF allows…
A machine learning based software pipeline to pick the variable ordering for algorithms with polynomial inputs
Dorian Florescu, Matthew England
We are interested in the application of Machine Learning (ML) technology to improve mathematical software. It may seem that the probabilistic nature of ML tools would invalidate th…