I am pursuing a Ph.D. program at The Gatsby Computational Neuroscience Unit under the supervision of Andrew SAXE and Caswell Barry my ambition is to embrace a research career in computational neuroscience. I have a master's degree in Theoretical Physics from the University of Manchester (UK).
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2023 - Cognitive Computational Neuroscience (CCN) Talk (Top 5%) Clémentine C. J. Dominé*, Rodrigo Carrasco* et al, ‘NeuralPlayground: A Standardised Environment for evaluation of Hippocampus and Entorhinal Cortex Models'
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2023 - Pre-Print Clémentine C. J. Dominé*, Marco Pegoraro* et al, ‘Geometric Epitope and Paratope Prediction’
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2023 - Accepted Talk Cosyne Implement an unsupervised point process model for replay detection of motor sequences in the dorsolateral striatum. Revealed first evidence for off-line consolidation of procedural memory in the dorsolateral striatum. Poster: https://drive.google.com/file/d/1lrTJrj3aGA_D3qDV4HNQCPv8NswaA2Qt/view?usp=sharing
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2023 - Accepted Poster Cosyne Clémentine C. J. Dominé, Rodrigo Carrasco* et al, 'NeuralPlayground: A Standardised Environment for evaluation of Hippocampus and Entorhinal Cortex Models'
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2022 - Accepted Neurips Exact learning dynamics of in Deep Linear Neural Network with Prior Knowledge. Paper: https://openreview.net/forum?id=58ohTfbDth
I am passionate and fascinated by the complex, flexible and optimized functioning of the brain that is yet left to be understood and characterized. I am particularly interested in studying the neural computational theories at the basis of information processing, learning and memory formation in neuronal networks. I am interested in answering questions such as: How is information from the environment represented by ensembles of neurons? How do the neural networks evolve with learning? How does the brain create, store, and update memories for places and events? I am looking forward to making advances in answering these questions, working at the intersection between theoretical neuroscience research and machine learning. It is my conviction that working on both artificial and biological neural networks in parallel will enable us to move forward faster in the general understanding of their mechanisms.
Geometric deep learning, Graph learning.
Google Scholar https://scholar.google.com/citations?user=oVZ0fSYAAAAJ&hl=en
Linkdin https://www.linkedin.com/in/clementine-domine-75a6a2150/
Site web https://clementinedomine.github.io
Twitter https://twitter.com/ClementineDomi6
Art loves science Web https://artlovessciences.github.io
Email [email protected] /[email protected]
Phone +33782510189