Proceedings of the International Conference on Neuromorphic Systems最新文献_第3页

Composing neural algorithms with Fugu 用Fugu编写神经算法

Proceedings of the International Conference on Neuromorphic Systems Pub Date : 2019-05-28 DOI: 10.1145/3354265.3354268

J. Aimone, William M. Severa, C. Vineyard

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引用次数: 18

Neuromorphic Acceleration for Approximate Bayesian Inference on Neural Networks via Permanent Dropout 基于永久Dropout的神经网络近似贝叶斯推理神经形态加速

Proceedings of the International Conference on Neuromorphic Systems Pub Date : 2019-04-29 DOI: 10.1145/3354265.3354274

Nathan Wycoff, Prasanna Balaprakash, Fangfang Xia

{"title":"Neuromorphic Acceleration for Approximate Bayesian Inference on Neural Networks via Permanent Dropout","authors":"Nathan Wycoff, Prasanna Balaprakash, Fangfang Xia","doi":"10.1145/3354265.3354274","DOIUrl":"https://doi.org/10.1145/3354265.3354274","url":null,"abstract":"As neural networks have begun performing increasingly critical tasks for society ranging from driving cars to identifying candidates for drug development, the value of their ability to perform uncertainty quantification (UQ) in their predictions has risen commensurately. Permanent dropout, a popular method for neural network UQ, involves injecting stochasticity into the inference phase of the model and creating many predictions for each of the test data. This shifts the computational and energy burden of deep neural networks from the training phase to the inference phase. Recent work has demonstrated near-lossless conversion of classical deep neural networks to their spiking counterparts. We use these results to demonstrate the feasibility of conducting the inference phase with permanent dropout on spiking neural networks, mitigating the technique's computational and energy burden, which is essential for its use at scale or on edge platforms. We demonstrate the proposed approach via the Nengo spiking neural simulator on a combination drug therapy dataset for cancer treatment, where UQ is critical. Our results indicate that the spiking approximation gives a predictive distribution practically indistinguishable from that given by the classical network.","PeriodicalId":225636,"journal":{"name":"Proceedings of the International Conference on Neuromorphic Systems","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121429650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Four Simulators of the DANNA Neuromorphic Computing Architecture DANNA神经形态计算体系结构的四个模拟器

Proceedings of the International Conference on Neuromorphic Systems Pub Date : 2018-07-23 DOI: 10.1145/3229884.3229893

A. Disney, J. Plank, Mark E. Dean

引用次数: 4

Modeling Memristor Radiation Interaction Events and the Effect on Neuromorphic Learning Circuits 记忆电阻辐射相互作用事件的建模及其对神经形态学习回路的影响

Proceedings of the International Conference on Neuromorphic Systems Pub Date : 2018-07-23 DOI: 10.1145/3229884.3229885

Sumedha Gandharava Dahl, Robert C. Ivans, K. D. Cantley

引用次数: 9

Towards adaptive spiking label propagation 面向自适应穗标签传播

Proceedings of the International Conference on Neuromorphic Systems Pub Date : 2018-07-23 DOI: 10.1145/3229884.3229897

Kathleen E. Hamilton, Catherine D. Schuman

引用次数: 5

Saccadic Predictive Vision Model with a Fovea 具有中央凹的跳跃性预测视觉模型

Proceedings of the International Conference on Neuromorphic Systems Pub Date : 2018-07-23 DOI: 10.1145/3229884.3229886

Michael Hazoglou, Todd Hylton

引用次数: 3

A Comparison of Neuromorphic Classification Tasks 神经形态分类任务的比较

Proceedings of the International Conference on Neuromorphic Systems Pub Date : 2018-07-23 DOI: 10.1145/3229884.3229896

John J. M. Reynolds, J. Plank, Catherine D. Schuman, Grant Bruer, A. Disney, Mark E. Dean, G. Rose

引用次数: 11

A Dynamical Systems Approach to Neuromorphic Computation of Conditional Probabilities 条件概率神经形态计算的动力系统方法

Proceedings of the International Conference on Neuromorphic Systems Pub Date : 2018-07-23 DOI: 10.1145/3229884.3229891

Nigel Stepp, Aruna Jammalamadaka

引用次数: 0

Learning Accuracy Analysis of Memristor-based Nonlinear Computing Module on Long Short-term Memory 基于忆阻器的长短期记忆非线性计算模块学习精度分析

Proceedings of the International Conference on Neuromorphic Systems Pub Date : 2018-07-23 DOI: 10.1145/3229884.3229889

Hongyu An, M. Al-Mamun, M. Orlowski, Y. Yi

引用次数: 7

Proceedings of the International Conference on Neuromorphic Systems 神经形态系统国际会议论文集

Proceedings of the International Conference on Neuromorphic Systems Pub Date : 2018-07-23 DOI: 10.1145/3229884

引用次数: 0