Zobrazeno 1 - 10
of 7 315
pro vyhledávání: '"A. D'Ascoli"'
Autor:
d'Ascoli, Stéphane, Bel, Corentin, Rapin, Jérémy, Banville, Hubert, Benchetrit, Yohann, Pallier, Christophe, King, Jean-Rémi
Deep learning has recently enabled the decoding of language from the neural activity of a few participants with electrodes implanted inside their brain. However, reliably decoding words from non-invasive recordings remains an open challenge. To tackl
Externí odkaz:
http://arxiv.org/abs/2412.17829
Publikováno v:
NeurIPS 2024
Originally formalized with symbolic representations, syntactic trees may also be effectively represented in the activations of large language models (LLMs). Indeed, a 'Structural Probe' can find a subspace of neural activations, where syntactically r
Externí odkaz:
http://arxiv.org/abs/2412.05571
Geometric trees are characterized by their tree-structured layout and spatially constrained nodes and edges, which significantly impacts their topological attributes. This inherent hierarchical structure plays a crucial role in domains such as neuron
Externí odkaz:
http://arxiv.org/abs/2408.08799
Autor:
Singh, Chandan, Ntinas, Vasileios, Prousalis, Dimitrios, Wang, Yongmin, Demirkol, Ahmet Samil, Messaris, Ioannis, Rana, Vikas, Menzel, Stephan, Ascoli, Alon, Tetzlaff, Ronald
This paper introduces an innovative graphical analysis tool for investigating the dynamics of Memristor Cellular Nonlinear Networks (M-CNNs) featuring 2nd-order processing elements, known as M-CNN cells. In the era of specialized hardware catering to
Externí odkaz:
http://arxiv.org/abs/2408.03260
ESM+: Modern Insights into Perspective on Text-to-SQL Evaluation in the Age of Large Language Models
The task of Text-to-SQL enables anyone to retrieve information from SQL databases using natural language. Despite several challenges, recent models have made remarkable advancements in this task using large language models (LLMs). Interestingly, we f
Externí odkaz:
http://arxiv.org/abs/2407.07313
Spiking neural networks drawing inspiration from biological constraints of the brain promise an energy-efficient paradigm for artificial intelligence. However, challenges exist in identifying guiding principles to train these networks in a robust fas
Externí odkaz:
http://arxiv.org/abs/2404.15627
Autor:
Wheeler, Diek W., Ascoli, Giorgio A.
Many fields, such as neuroscience, are experiencing the vast proliferation of cellular data, underscoring the need for organizing and interpreting large datasets. A popular approach partitions data into manageable subsets via hierarchical clustering,
Externí odkaz:
http://arxiv.org/abs/2403.03318
Autor:
Messaris, Ioannis, Ascoli, Alon, Demirkol, Ahmet S., Ntinas, Vasileios, Prousalis, Dimitrios, Tetzlaff, Ronald
In this theoretical study, we focus on the high-frequency response of the electrothermal NbO2-Mott threshold switch, a real-world electronic device, which has been proved to be relevant in several applications and is classified as a volatile memristo
Externí odkaz:
http://arxiv.org/abs/2401.10924
Autor:
Yufeng Liu, Shengdian Jiang, Yingxin Li, Sujun Zhao, Zhixi Yun, Zuo-Han Zhao, Lingli Zhang, Gaoyu Wang, Xin Chen, Linus Manubens-Gil, Yuning Hang, Qiaobo Gong, Yuanyuan Li, Penghao Qian, Lei Qu, Marta Garcia-Forn, Wei Wang, Silvia De Rubeis, Zhuhao Wu, Pavel Osten, Hui Gong, Michael Hawrylycz, Partha Mitra, Hongwei Dong, Qingming Luo, Giorgio A. Ascoli, Hongkui Zeng, Lijuan Liu, Hanchuan Peng
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-23 (2024)
Abstract We conducted a large-scale whole-brain morphometry study by analyzing 3.7 peta-voxels of mouse brain images at the single-cell resolution, producing one of the largest multi-morphometry databases of mammalian brains to date. We registered 20
Externí odkaz:
https://doaj.org/article/87a31a838adf4b4a8950e35559371dc9
We introduce ODEFormer, the first transformer able to infer multidimensional ordinary differential equation (ODE) systems in symbolic form from the observation of a single solution trajectory. We perform extensive evaluations on two datasets: (i) the
Externí odkaz:
http://arxiv.org/abs/2310.05573