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In-Situ Implementation and Training of Convolutional Neural Network on FPGAs
The main objective of this thesis is to investigate the efficiency of in-situ trainable Convolutional Neural Networks (CNNs) on modern programmable System-on-Chip (SoC) Field Programmable Gate Arrays (FPGAs) composed of ...
Full Wavefield Reconstruction and Full Waveform Inversion
Two-way reverse time extrapolation of the recorded seismic data is the essential step in seismic reverse time migration (RTM). Various RTM algorithms have been developed to produce accurate image locations rather than ...
Efficient Combination of Neural and Symbolic Learning for Relational Data
Much has been achieved in AI but to realize its true potential, it is imperative that the AI system should be able to learn generalizable and actionable higher-level knowledge from lowest level percepts. Inspired by this ...
Quantum Phases of Time-Reversal Invariant Bose-Einstein Condensates
Recent experimental realization of spin-orbit coupling (SOC) for ultracold atomic gases with the use of synthetic gauge fields provides a powerful platform for the study of novel quantum phenomena and the simulation of ...