Sökning: "first class skolan"
Visar resultat 1 - 5 av 65 uppsatser innehållade orden first class skolan.
1. Comparison of Output Decoding Techniques for Spiking Neural Networks
Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Spiking Neural Networks (SNNs) hold significant potential due to their high energy efficiency when implemented on specialized hardware. Central to SNNs is the translation of sequences of spike events to concrete outputs, like class predictions. LÄS MER
2. Exploring Normalizing Flow Modifications for Improved Model Expressivity
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Normalizing flows represent a class of generative models that exhibit a number of attractive properties, but do not always achieve state-of-the-art performance when it comes to perceived naturalness of generated samples. To improve the quality of generated samples, this thesis examines methods to enhance the expressivity of discrete-time normalizing flow models and thus their ability to capture different aspects of the data. LÄS MER
3. Control Barrier Functions for Formation Control of Leader-follower Multi-agent Systems
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : This thesis studies formation control for a class of general leader-follower multi-agent systems with Control Barrier Functions (CBFs) such that connectivity maintenance is fulfilled for all the neighboring agents. In leader-follower multi-agent systems, only the leader agents are controlled by the externally designed input, while the followers are guided through their dynamic couplings with the neighboring agents. LÄS MER
4. Structural Comparison of Data Representations Obtained from Deep Learning Models
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : In representation learning we are interested in how data is represented by different models. Representations from different models are often compared by training a new model on a downstream task using the representations and testing their performance. LÄS MER
5. Explanation Methods for a Medical Image Classifier by Analysis of its Uncertainty
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Over the last decade, neural networks have reached almost every field of science and technology. They have become a crucial part of various real-world applications, such as medical imaging. LÄS MER