Essays about: "message passing"
Showing result 1 - 5 of 61 essays containing the words message passing.
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1. Low-latency transport protocols inactor systems : Performance evaluation of QUIC in Kompact
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Developers widely use actor frameworks to build highly distributed systems. However, modern actor frameworks are limited in their network implementations, with Transmission Control Protocol (TCP) and User Datagram Protocol (UDP) being the main protocols used for network communication. READ MORE
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2. Design and Evaluation of Peptide Binders : In silico evaluation and comparison of generative AI for de novo peptide binder design
University essay from Uppsala universitet/Beräkningsbiologi och bioinformatikAbstract : Peptide binders are short proteins that bind to larger proteins. Due to peptide binders having high specificity and being cheap to synthesize, they are a prime candidate for drug design. Creating new proteins in silico can be divided into three steps: protein backbone generation, sequence design, and computational filtering. READ MORE
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3. Phase Unwrapping MRI Flow Measurements
University essay from Uppsala universitet/Avdelningen Vi3Abstract : Magnetic resonance images (MRI) are acquired by sampling the current of induced electromotiveforce (EMF). EMF is induced due to flux of the net magnetic field from coherent nuclear spins with intrinsic magnetic dipole moments. READ MORE
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4. Link Prediction Using Learnable Topology Augmentation
University essay from KTH/Matematik (Avd.)Abstract : Link prediction is a crucial task in many downstream applications of graph machine learning. Graph Neural Networks (GNNs) are a prominent approach for transductive link prediction, where the aim is to predict missing links or connections only within the existing nodes of a given graph. READ MORE
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5. Expressibility of multiscale physics in deep networks
University essay from Umeå universitet/Institutionen för fysikAbstract : Motivated by the successes in the field of deep learning, the scientific community has been increasingly interested in neural networks that are able to reason about physics. As neural networks are universal approximators, they could in theory learn representations that are more efficient than traditional methods whenever improvements are theoretically possible. READ MORE