Implementation of linear filters in the spike domain. - Dorian Florescu; Daniel Coca (ECC, 2015)

A Novel Reconstruction Framework for Time-Encoded Signals with Integrate-and-Fire Neurons. - Dorian Florescu; Daniel Coca (Neural Comput., 2015)

Identification of Linear and Nonlinear Sensory Processing Circuits from Spiking Neuron Data. - Dorian Florescu; Daniel Coca (Neural Comput., 2018)

Improved Cross-Validation for Classifiers that Make Algorithmic Choices to Minimise Runtime Without Compromising Output Correctness. - Dorian Florescu; Matthew England 001 (MACIS, 2019)

Machine Learning to Improve Cylindrical Algebraic Decomposition in Maple. - Matthew England 001; Dorian Florescu (MC, 2019)

Comparing Machine Learning Models to Choose the Variable Ordering for Cylindrical Algebraic Decomposition. - Matthew England 001; Dorian Florescu (CICM, 2019)

Algorithmically Generating New Algebraic Features of Polynomial Systems for Machine Learning. - Dorian Florescu; Matthew England 001 (SC-square@SIAM AG, 2019)

Learning with Precise Spike Times: A New Decoding Algorithm for Liquid State Machines. - Dorian Florescu; Daniel Coca (Neural Comput., 2019)

A Machine Learning Based Software Pipeline to Pick the Variable Ordering for Algorithms with Polynomial Inputs. - Dorian Florescu; Matthew England 001 (ICMS, 2020)

Unlimited Sampling with Hysteresis. - Dorian Florescu; Felix Krahmer; Ayush Bhandari (ACSCC, 2021)

Event-Driven Modulo Sampling. - Dorian Florescu; Felix Krahmer; Ayush Bhandari (ICASSP, 2021)

Unlimited Sampling with Local Averages. - Dorian Florescu; Ayush Bhandari (ICASSP, 2022)

Modulo Event-Driven Sampling: System Identification and Hardware Experiments. - Dorian Florescu; Ayush Bhandari (ICASSP, 2022)

Unlimited Sampling via Generalized Thresholding. - Dorian Florescu; Ayush Bhandari (ISIT, 2022)

Multi-Dimensional Unlimited Sampling and Robust Reconstruction. - Dorian Florescu; Ayush Bhandari (CoRR, 2022)

Time Encoding via Unlimited Sampling: Theory, Algorithms and Hardware Validation. - Dorian Florescu; Ayush Bhandari (IEEE Trans. Signal Process., 2022)

The Surprising Benefits of Hysteresis in Unlimited Sampling: Theory, Algorithms and Experiments. - Dorian Florescu; Felix Krahmer; Ayush Bhandari (IEEE Trans. Signal Process., 2022)

Unlimited Sampling of Bandpass Signals: Computational Demodulation via Undersampling. - Gal Shtendel; Dorian Florescu; Ayush Bhandari (IEEE Trans. Signal Process., 2023)

Constrained Neural Networks for Interpretable Heuristic Creation to Optimise Computer Algebra Systems. - Dorian Florescu; Matthew England 001 (ICMS, 2024)

Multichannel Modulo Sampling with Unlimited Noise. - Dorian Florescu (ICASSP, 2025)

A Generalized Approach for Recovering Time Encoded Signals With Finite Rate of Innovation. - Dorian Florescu (IEEE Trans. Signal Process., 2025)