no code implementations • 22 May 2024 • Lars Graf, Zhe Su, Giacomo Indiveri
The drive to develop artificial neural networks that efficiently utilize resources has generated significant interest in bio-inspired Spiking Neural Networks (SNNs).
no code implementations • 8 Mar 2024 • Xuhui Zhou, Zhe Su, Tiwalayo Eisape, Hyunwoo Kim, Maarten Sap
Recent advances in large language models (LLM) have enabled richer social simulations, allowing for the study of various social phenomena.
no code implementations • 8 Aug 2023 • Zhe Su, Hyunjung Hwang, Tristan Torchet, Giacomo Indiveri
In particular the core interface that manages inter-core spike communication is a crucial component as it represents the bottleneck of Power-Performance-Area (PPA) especially for the arbitration architecture and the routing memory.
1 code implementation • 25 May 2023 • Yan Liu, Yan Gao, Zhe Su, Xiaokang Chen, Elliott Ash, Jian-Guang Lou
In this work, we aim to uncover and categorize social biases in Text-to-SQL models.
no code implementations • 11 Oct 2022 • Zhenbang Wu, Huaxiu Yao, Zhe Su, David M Liebovitz, Lucas M Glass, James Zou, Chelsea Finn, Jimeng Sun
However, newly approved drugs do not have much historical prescription data and cannot leverage existing drug recommendation methods.
no code implementations • 29 Aug 2022 • Vanessa R. C. Leite, Zhe Su, Adrian M. Whatley, Giacomo Indiveri
To minimize the use of memory resources in multi-core neuromorphic processors, we propose a network design approach inspired by biological neural networks.
1 code implementation • 5 Jun 2022 • Ziyue Jiang, Zhe Su, Zhou Zhao, Qian Yang, Yi Ren, Jinglin Liu, Zhenhui Ye
This paper tackles the polyphone disambiguation problem from a concise and novel perspective: we propose Dict-TTS, a semantic-aware generative text-to-speech model with an online website dictionary (the existing prior information in the natural language).
no code implementations • 1 Mar 2022 • Vanessa R. C. Leite, Zhe Su, Adrian M. Whatley, Giacomo Indiveri
Both in electronics and biology, physical implementations of neural networks have severe energy and memory constraints.
1 code implementation • 20 Sep 2021 • Kristen M. Campbell, Haocheng Dai, Zhe Su, Martin Bauer, P. Thomas Fletcher, Sarang C. Joshi
In order to enable population-level statistical analysis of the structural connectome, we propose representing a connectome as a Riemannian metric, which is a point on an infinite-dimensional manifold.
no code implementations • 9 Mar 2021 • Kristen M. Campbell, Haocheng Dai, Zhe Su, Martin Bauer, P. Thomas Fletcher, Sarang C. Joshi
The structural connectome is often represented by fiber bundles generated from various types of tractography.
1 code implementation • 4 Oct 2019 • Zhe Su, Martin Bauer, Stephen C. Preston, Hamid Laga, Eric Klassen
In this article we introduce a family of elastic metrics on the space of parametrized surfaces in 3D space using a corresponding family of metrics on the space of vector valued one-forms.
Differential Geometry Optimization and Control 49Q10, 58B20