activity
20182026
most citedDynamical Systems and Neural Networks

4 citations · 5 across the 5 of their papers we have counts for

collaborators

8 papers

math.OC2026

Man, Machine, and Mathematics

Akshunna S. Dogra

Nonlinear models and optimization methods have successfully tackled a rapidly growing set of problems in recent years. Indeed, a relatively small toolbox of such models and methods…

q-bio.NC2025

Distance by de-correlation: Computing distance with heterogeneous grid cells

Pritipriya Dasbehera, Akshunna S. Dogra, William T. Redman

Encoding the distance between locations in space is essential for accurate navigation. Grid cells, a functional class of neurons in medial entorhinal cortex, are believed to suppor…

cs.LG2025

FINDER: Feature Inference on Noisy Datasets using Eigenspace Residuals

Trajan Murphy, Akshunna S. Dogra, Hanfeng Gu +3

''Noisy'' datasets (regimes with low signal to noise ratios, small sample sizes, faulty data collection, etc) remain a key research frontier for classification methods with both th…

cs.LG2020

Local error quantification for Neural Network Differential Equation solvers

Akshunna S. Dogra, William T Redman

Neural networks have been identified as powerful tools for the study of complex systems. A noteworthy example is the neural network differential equation (NN DE) solver, which can…

math.DS20204 cited

Dynamical Systems and Neural Networks

Akshunna S. Dogra

Neural Networks (NNs) have been identified as a potentially powerful tool in the study of complex dynamical systems. A good example is the NN differential equation (DE) solver, whi…

quant-ph2020

Impact of ionizing radiation on superconducting qubit coherence

Antti Vepsäläinen, Amir H. Karamlou, John L. Orrell +11

The practical viability of any qubit technology stands on long coherence times and high-fidelity operations, with the superconducting qubit modality being a leading example. Howeve…