Results 11 to 20 of about 27,364 (268)
Quantized Graph Neural Networks for Image Classification
Mathematics, 2023 Researchers have resorted to model quantization to compress and accelerate graph neural networks (GNNs). Nevertheless, several challenges remain: (1) quantization functions overlook outliers in the distribution, leading to increased quantization errors; (
Xinbiao Xu +3 more
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BMC Plant Biology, 2023 Background Rhamnus utilis Decne (Rhamnaceae) is an ecologically and economically important tree species. The growing market demands and recent anthropogenic impacts to R. utilis forests has negatively impacted its populations severely. However, little is
Song Guiquan +7 more
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How to Secure Valid Quantizations
Entropy, 2022 Canonical quantization has created many valid quantizations that require infinite-line coordinate variables. However, the half-harmonic oscillator, which is limited to the positive coordinate half, cannot receive a valid canonical quantization because of
John R. Klauder
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A dichotomy color quantization algorithm for the HSI color space
Scientific Reports, 2023 Color quantization is used to obtain an image with the same number of pixels as the original but represented using fewer colors. Most existing color quantization algorithms are based on the Red Green Blue (RGB) color space, and there are few color ...
Xia Yu +5 more
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Gradient Estimation for Ultra Low Precision POT and Additive POT Quantization
IEEE Access, 2023 Deep learning networks achieve high accuracy for many classification tasks in computer vision and natural language processing. As these models are usually over-parameterized, the computations and memory required are unsuitable for power-constrained ...
Huruy Tesfai +4 more
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Learning Bilateral Clipping Parametric Activation for Low-Bit Neural Networks
Mathematics, 2023 Among various network compression methods, network quantization has developed rapidly due to its superior compression performance. However, trivial activation quantization schemes limit the compression performance of network quantization.
Yunlong Ding, Di-Rong Chen
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From Quantized DNNs to Quantizable DNNs [PDF]
Proceedings of the British Machine Vision Conference 2020, 2020 This paper proposes Quantizable DNNs, a special type of DNNs that can flexibly quantize its bit-width (denoted as `bit modes' thereafter) during execution without further re-training. To simultaneously optimize for all bit modes, a combinational loss of all bit modes is proposed, which enforces consistent predictions ranging from low-bit mode to 32-bit
Kunyuan Du, Ya Zhang 0002, Haibing Guan
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Design Exploration of ReRAM-Based Crossbar for AI Inference
IEEE Access, 2021 ReRAM-based crossbar designs utilizing mixed-signal implementation has gained importance due to their low power, small size, low cost, and high throughput especially for multiply-and-add operations in AI-related applications.
Yasmin Halawani +2 more
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Proceedings of the National Academy of Sciences, 2003 We associate to the action of a compact Lie group G on a line bundle over a compact oriented even-dimensional manifold a virtual representation of G using a twisted version of the signature operator.
Guillemin, Victor +2 more
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Quantization and Deployment of Deep Neural Networks on Microcontrollers
Sensors, 2021 Embedding Artificial Intelligence onto low-power devices is a challenging task that has been partly overcome with recent advances in machine learning and hardware design.
Pierre-Emmanuel Novac +4 more
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