C
Claudia Clopath
Researcher at Imperial College London
Publications - 166
Citations - 11996
Claudia Clopath is an academic researcher from Imperial College London. The author has contributed to research in topics: Computer science & Biology. The author has an hindex of 30, co-authored 134 publications receiving 7728 citations. Previous affiliations of Claudia Clopath include Columbia University & Royal School of Mines.
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Image Synthesis with a Convolutional Capsule Generative Adversarial Network
Cher Bass,Tianhong Dai,Benjamin Billot,Kai Arulkumaran,Antonia Creswell,Claudia Clopath,Vincenzo De Paola,Anil A. Bharath +7 more
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Action prediction error: a value-free dopaminergic teaching signal that drives stable learning
Francesca Greenstreet,Hernando Martínez Vergara,Sthitapranjya Pati,Laura Schwarz,Matthew Wisdom,Fred Marbach,Yvonne Johansson,Lars Rollik,Ted Moskovitz,Claudia Clopath,Marcus Stephenson-Jones +10 more
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A tale of two transmitters: serotonin and histamine as in vivo biomarkers of chronic stress in mice
Melinda Hersey,Melissa Reneaux,Shane N. Berger,Sergio Mena,Anna Marie Buchanan,Yangguang Ou,Navid Tavakoli,Lawrence P. Reagan,Claudia Clopath,Parastoo Hashemi +9 more
TL;DR: In this article , in-vivo serotonin and histamine voltammetric measurement technologies, behavioral testing, and cutting-edge mathematical methods were used to correlate chemistry to stress and behavior.
Posted ContentDOI
Learning spatiotemporal signals using a recurrent spiking network that discretizes time
TL;DR: A model using biological-plausible plasticity rules for a specific computational task: spatiotemporal sequence learning is investigated where a spiking recurrent network of excitatory and inhibitory biophysical neurons drives a read-out layer: the dynamics of the recurrent network is constrained to encode time while the read- out neurons encode space.
Deep Reinforcement Learning for Subpixel Neural Tracking
Tianhong Dai,Magda Dubois,Kai Arulkumaran,Jonathan Campbell,Cher Bass,Benjamin Billot,Fatmatulzehra Uslu,Vincenzo De Paola,Claudia Clopath,Anil A. Bharath +9 more
TL;DR: In this article, deep reinforcement learning is used to learn how to track at the subpixel level for axon detection in a synthetic environment, and apply it to tracing axons.