Essays about: "Latent Space"
Showing result 6 - 10 of 74 essays containing the words Latent Space.
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6. Deep convolution neural network for attention decoding in multi-channel EEG with conditional variational autoencoder for data augmentation
University essay from Lunds universitet/Institutionen för reglerteknikAbstract : Objectives: This project aims to develop a deep learning-based attention decoding system that can distinguish between noise and speech in noise and also identify the direction of attended speech from the brain data recorded with electroencephalography (EEG) instruments. Two deep convolutional neural network (DCNN) models will be designed: (1) one DCNN model capable of classifying incoming segments of sound as speech or speech in background noise, and (2) one DCNN model identifying the direction (left vs. READ MORE
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7. Improving Change Point Detection Using Self-Supervised VAEs : A Study on Distance Metrics and Hyperparameters in Time Series Analysis
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : This thesis addresses the optimization of the Variational Autoencoder-based Change Point Detection (VAE-CP) approach in time series analysis, a vital component in data-driven decision making. We evaluate the impact of various distance metrics and hyperparameters on the model’s performance using a systematic exploration and robustness testing on diverse real-world datasets. READ MORE
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8. Overcoming The New Item Problem In Recommender Systems : A Method For Predicting User Preferences Of New Items
University essay from Stockholms universitet/Statistiska institutionenAbstract : This thesis addresses the new item problem in recommender systems, which pertains to the challenges of providing personalized recommendations for items which have limited user interaction history. The study proposes and evaluates a method for generating personalized recommendations for movies, shows, and series on one of Sweden’s largest streaming platforms. READ MORE
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9. Matching Trades with Confirmations via Contrastive Learning : Asymmetric Contrastive Learning on Text Data
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : In the banking world trades of securities are finalized every day, on behalf of the banks themselves or of their clients. When the trades have been booked by the front office the confirmations sent by the counterparty have to be checked and connected to the correct trade by hand, posing the question whether this process could not be automated using machine learning techniques. READ MORE
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10. Messing With The Gap: On The Modality Gap Phenomenon In Multimodal Contrastive Representation Learning
University essay from Uppsala universitet/Industriell teknikAbstract : In machine learning, a sub-field of computer science, a two-tower architecture model is a specialised type of neural network model that encodes paired data from different modalities (like text and images, sound and video, or proteomics and gene expression profiles) into a shared latent representation space. However, when training these models using a specific contrastive loss function, known as the multimodalinfoNCE loss, seems to often lead to a unique geometric phenomenon known as the modality gap. READ MORE
