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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Journal ArticleDOI
AI for social good: unlocking the opportunity for positive impact.
Nenad Tomasev,Julien Cornebise,Frank Hutter,Frank Hutter,Shakir Mohamed,Angela Picciariello,Bec Connelly,Danielle Belgrave,Daphne Ezer,Daphne Ezer,Fanny Cachat van der Haert,Frank Mugisha,Gerald Abila,Hiromi Arai,Hisham Almiraat,Julia Proskurnia,Kyle Snyder,Mihoko Otake-Matsuura,Mustafa Othman,Tobias Glasmachers,Wilfried de Wever,Yee Whye Teh,Mohammad Emtiyaz Khan,Ruben De Winne,Tom Schaul,Claudia Clopath +25 more
TL;DR: This work provides a set of guidelines for establishing successful long-term collaborations between AI researchers and application-domain experts, relate them to existing AI4SG projects and identify key opportunities for future AI applications targeted towards social good.
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Voltage and Spike Timing Interact in STDP – A Unified Model
TL;DR: It is hypothesized that the voltage dependence can explain differential effects of STDP in dendrites, since the amplitude and time course of backpropagating action potentials or dendritic spikes influences the plasticity results in the model.
Journal ArticleDOI
Supervised learning in spiking neural networks with FORCE training
Wilten Nicola,Claudia Clopath +1 more
TL;DR: For example, in this article, the FORCE method is applied to spiking neural networks to mimic dynamical systems, classify inputs, and store discrete sequences that correspond to the notes of a song.
Journal ArticleDOI
Variance and invariance of neuronal long-term representations
TL;DR: It is shown that stable baseline representations and precise recovery from perturbations in visual cortex could arise from a ‘backbone’ of strong recurrent connectivity between similarly tuned cells together with a small number of ‘anchor’ neurons exempt from plastic changes.
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Activity-Dependent Downscaling of Subthreshold Synaptic Inputs during Slow-Wave-Sleep-like Activity In Vivo
Ana González-Rueda,Ana González-Rueda,Victor Pedrosa,Victor Pedrosa,Rachael C. Feord,Claudia Clopath,Ole Paulsen +6 more
TL;DR: It is found that this novel activity-dependent and input-specific downscaling mechanism has two important computational advantages: improved signal-to-noise ratio, and preservation of previously stored information.