Robert L. Peach

Orcid: 0000-0002-8738-5825

According to our database1, Robert L. Peach authored at least 16 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Algorithm 1044: PyGenStability, a Multiscale Community Detection Framework with Generalized Markov Stability.
ACM Trans. Math. Softw., June, 2024

Head movement dynamics in dystonia: a multi-centre retrospective study using visual perceptive deep learning.
npj Digit. Medicine, 2024

Validation and application of computer vision algorithms for video-based tremor analysis.
npj Digit. Medicine, 2024

Enhancing security in brain-computer interface applications with deep learning: Electroencephalogram-based user identification.
Expert Syst. Appl., 2024

Information-Theoretic Measures on Lattices for High-Order Interactions.
CoRR, 2024

Implicit Gaussian process representation of vector fields over arbitrary latent manifolds.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
Interpretable statistical representations of neural population dynamics and geometry.
CoRR, 2023

PyGenStability: Multiscale community detection with generalized Markov Stability.
CoRR, 2023

Interaction Measures, Partition Lattices and Kernel Tests for High-Order Interactions.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2021
HCGA: Highly comparative graph analysis for network phenotyping.
Patterns, 2021

Listening to Mental Health Crisis Needs at Scale: Using Natural Language Processing to Understand and Evaluate a Mental Health Crisis Text Messaging Service.
Frontiers Digit. Health, 2021

Network memory in the movement of hospital patients carrying antimicrobial-resistant bacteria.
Appl. Netw. Sci., 2021

2020
Data-driven modelling and characterisation of task completion sequences in online courses.
CoRR, 2020

2019
Semi-supervised classification on graphs using explicit diffusion dynamics.
CoRR, 2019

Graph centrality is a question of scale.
CoRR, 2019

Data-driven unsupervised clustering of online learner behaviour.
CoRR, 2019


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