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Showing result 6 - 10 of 109 essays matching the above criteria.
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6. Improving the Synthesis of Annotations for Partially Automated Deductive Verification
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : This work investigates possible improvements to an existing annotation inference tool. The tool is part of a toolchain that aims to automate the process of software verification using formal methods. READ MORE
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7. Regularizing Vision-Transformers Using Gumbel-Softmax Distributions on Echocardiography Data
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : This thesis introduces an novel approach to model regularization in Vision Transformers (ViTs), a category of deep learning models. It employs stochastic embedded feature selection within the context of echocardiography video analysis, specifically focusing on the EchoNet-Dynamic dataset. READ MORE
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8. Effects of Varying Precision on a FPGA using the SpMXV problem : A comparative study
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : With Moore’s Law slowing down, designing computer hardware that keeps up with the performance demands is becoming increasingly difficult. An interesting area of research is the Field Programmable Gate Array (FPGA) which is a re-programmable hardware device, and which might not be as dependent on Moore’s Law as other hardware. READ MORE
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9. Investigation of 8-bit Floating-Point Formats for Machine Learning
University essay from Linköpings universitet/DatorteknikAbstract : Applying machine learning to various applications has gained significant momentum in recent years. However, the increasing complexity of networks introduces challenges such as a larger memory footprint and decreased throughput. This thesis aims to address these challenges by exploring the use of 8-bit floating-point numbers for machine learning. READ MORE
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10. Expression Simplification Using E-Graphs for Interval Evaluation
University essay from Uppsala universitet/Institutionen för informationsteknologiAbstract : Daisy is a framework for verifying and bounding the magnitudes of rounding errors introduced by floating-point arithmetic in numerical programs. As part of this, Daisy employs a rudimentary algorithm for simplifying expressions derived from the programs. READ MORE