Essays about: "inference efficiency"
Showing result 1 - 5 of 33 essays containing the words inference efficiency.
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1. Low-power Acceleration of Convolutional Neural Networks using Near Memory Computing on a RISC-V SoC
University essay from Lunds universitet/Institutionen för elektro- och informationsteknikAbstract : The recent peak in interest for artificial intelligence, partly fueled by language models such as ChatGPT, is pushing the demand for machine learning and data processing in everyday applications, such as self-driving cars, where low latency is crucial and typically achieved through edge computing. The vast amount of data processing required intensifies the existing performance bottleneck of the data movement. READ MORE
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2. Analysing Regime-Switching and Cointegration with Hamiltonian Monte Carlo
University essay from Uppsala universitet/Statistiska institutionenAbstract : The statistical analysis of cointegration is crucial for inferring shared stochastic trends between variables and is an important area of Econometrics for analyzing long-term equilibriums in the economy. Bayesian inference of cointegration involves the identification of cointegrating vectors that are determined up to arbitrary linear combinations, for which the Gibbs sampler is often used to simulate draws from the posterior distribution. READ MORE
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3. Failure Inference in Drilling Bits: : Leveraging YOLO Detection for Dominant Failure Analysis
University essay from Uppsala universitet/Institutionen för informationsteknologiAbstract : Detecting failures in tricone drill bits is crucial in the mining industry due to their potential consequences, including operational losses, safety hazards, and delays in drilling operations. Timely identification of failures allows for proactive maintenance and necessary measures to ensure smooth drilling processes and minimize associated risks. READ MORE
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4. A Bidirectional ApproachApplied on Deeper and WiderSiamese Network
University essay from Uppsala universitet/Institutionen för informationsteknologiAbstract : Object tracking and object detection are two components within computer vision that have been widely improved during the last decade, in terms of precision and speed. This is mainly because deep learning has been incorporatedinto the algorithms, but also because new techniques and insights within the area are frequently released. READ MORE
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5. Dynamic Covariance Modelling Using Generalised Wishart Processes
University essay from Lunds universitet/Matematisk statistikAbstract : Modern portfolio theory was pioneered by Markowitz who formulated the mean-variance problem, without which any discussion on quantitative approaches to portfolio selection would be incomplete. The framework boils down to finding the expected return $\mu$ and covariance $\Sigma$, after which the solution is proportional to $\Sigma^{-1}\mu$. READ MORE
