Essays about: "learning toy"
Showing result 1 - 5 of 17 essays containing the words learning toy.
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1. On Linear Mode Connectivity up to Permutation of Hidden Neurons in Neural Network : When does Weight Averaging work?
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Neural networks trained using gradient-based optimization methods exhibit a surprising phenomenon known as mode connectivity, where two independently trained network weights are not isolated low loss minima in the parameter space. Instead, they can be connected by simple curves along which the loss remains low. READ MORE
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2. An Open-Source Autoencoder Compression Tool for High Energy Physics
University essay from Lunds universitet/Partikel- och kärnfysik; Lunds universitet/Fysiska institutionenAbstract : A common problem across scientific fields and industries is data storage. This thesis presents an open-source lossy data compression tool with its foundation in Machine Learning - Baler. Baler has been used to compress High Energy Physics (HEP) data, and initial compression tests on Computational Fluid Dynamics (CFD) toy data have been performed. READ MORE
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3. 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
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4. Analyzing the Negative Log-Likelihood Loss in Generative Modeling
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Maximum-Likelihood Estimation (MLE) is a classic model-fitting method from probability theory. However, it has been argued repeatedly that MLE is inappropriate for synthesis applications, since its priorities are at odds with important principles of human perception, and that, e.g. READ MORE
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5. Data-driven methods for estimation of dynamic OD matrices
University essay from Linköpings universitet/Kommunikations- och transportsystem; Linköpings universitet/Tekniska fakultetenAbstract : The idea behind this report is based on the fact that it is not only the number of users in the traffic network that is increasing, the number of connected devices such as probe vehicles and mobile sources has increased dramatically in the last decade. These connected devices provide large-scale mobility data and new opportunities to analyze the current traffic situation as they traverse through the network and continuously send out different types of information like Global Positioning System (GPS) data and Mobile Network Data (MND). READ MORE
