Essays about: "fully connected networks"
Showing result 11 - 15 of 54 essays containing the words fully connected networks.
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11. Explaining Neural Networks used for PIM Cancellation
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Passive Intermodulation is a type of distortion affecting the sensitive receiving signals in a cellular network, which is a growing problem in the telecommunication field. One way to mitigate this problem is through Passive Intermodulation Cancellation, where the predicted noise in a signal is modeled with polynomials. READ MORE
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12. Assessing BERT-Style Models' Abilities to Learn the Number of a Subject
University essay from Uppsala universitet/Institutionen för lingvistik och filologiAbstract : There is an increasing interest in using deep neural networks in various downstream natural language processing tasks. Such models are commonly used as black boxes, meaning that their decision-making is difficult to interpret. In order to build trust in models, it is crucial to analyse their inner workings which lead to predictions. READ MORE
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13. A Statistical and Machine Learning Approach to Air Pollution Forecasts
University essay from Stockholms universitet/Institutionen för data- och systemvetenskapAbstract : In today’s world, where air pollution has become a ubiquitous problem, city air is normally monitored. Such monitoring can produce large amounts of data, and this enables the development of statistical and machine learning techniques for modeling and forecasting air quality. READ MORE
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14. Artificial Value-at-Risk : Using Neural Networks to Replicate Filtered Historical Simulation for Value-at-Risk Calculations
University essay from Umeå universitet/Institutionen för matematik och matematisk statistikAbstract : Since financial markets are considered risky, there is a need to have credible tools that can estimate these risks. For a Central Clearing Counterparty it is of utmost importance to conduct accurate estimations of its members’ risk exposures to deter-mine their margin requirements. READ MORE
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15. The derivation of first- and second-order backpropagation methods for fully-connected and convolutional neural networks
University essay from Lunds universitet/Matematik LTH; Lunds universitet/MatematikcentrumAbstract : We introduce rigorous theory for deriving first and second order backpropagation methods for Deep Neural Networks (DNN) whilst satisfying existing theory in DNN optimization. We begin by formally defining a neural network with its respective components and state the first and second order chain rule with respect to its partial derivatives. READ MORE
