Index Catalog // ScholarsArchive@OSU

Semantic embodied navigation : developing agents that navigate from language and vision

Creator:: Krantz, Jacob
Abstract:: Autonomous robotic agents are on their way to becoming in-home personal assistants, construction assistants, and warehouse workers. The degree of autonomy of such systems is reflected by the manner in which we specify goals to them; the abstraction of low-level commands to high-level goals goes hand-in-hand with increased autonomy. In...
Resource Type:: Dissertation

Automatic Explanations of Computation Results with Value Decompositions and Dominating Sets

Creator:: Kumar, Prashant
Abstract:: In an increasingly computation-driven world, algorithms and mathematical models significantly impact decision making across various fields. To foster trust and understanding, it is crucial to provide users with clear and concise explanations of the reasoning behind the results produced by computational tools, especially when recommendations appear counterintuitive. Legal frameworks in...
Resource Type:: Dissertation

Characterizing and Addressing Dataset Shift with Deep Learning

Creator:: Olson, Matthew L.
Abstract:: This dissertation delves into understanding, characterizing, and addressing dataset shift in deep learning, a pervasive issue for deployed machine learning systems. Integral aspects of the problem are examined: We start with the use of counterfactual explanations in order to characterize the behavior of deep reinforcement learning agents in visual input...
Resource Type:: Dissertation

Generative Models Meet Explainable AI and Long-Tail Learning: from Attribution Maps to Image Synthesis

Creator:: Khorram, Saeed
Abstract:: The advancement of artificial intelligence (AI) has led to transformative developments across multiple sectors, fostering innovation and redefining our interactions with technology. As AI matures and becomes integrated into society, it offers numerous opportunities to address global challenges and revolutionize a wide array of human endeavors. These advances are driven...
Resource Type:: Dissertation

Agile Bipedal Locomotion via Hierarchical Control by Incorporating Physical Principles, Learning, and Optimization

Creator:: Green, Kevin
Abstract:: Robotic Bipedal locomotion holds the potential for efficient, robust traversal of difficult terrain. The difficulty lies in the dynamics of locomotion which complicate control and motion planning. Bipedal locomotion dynamics are dimensionally large problems, extremely nonlinear, and operate on the limits of actuator capabilities, which limit the performance of generic...
Resource Type:: Dissertation

Deep Learning for Human and Biological Languages

Creator:: Hong, Junki
Abstract:: We explore the application of deep learning to the disparate fields of natural language processing and computational biology. Both the sentences uttered by humans as well as the RNA and protein sequences found within the cells of their bodies can be considered formal languages in computer science, as sets of...
Resource Type:: Dissertation

Deep Convolutional Network on Point Clouds for 3D Scene Understanding

Creator:: Wu, Wenxuan
Abstract:: As one of the most popular data types, the point cloud is widely used in various appli- cations, including computer vision, computer graphics and robotics. The capability to directly measure 3D point clouds is invaluable in those applications as depth information could remove a lot of the segmentation ambiguities in...
Resource Type:: Dissertation

Uncertainty in Deep Learning with Implicit Neural Networks

Creator:: Ratzlaff, Neale
Abstract:: The ability to extract uncertainties from predictions is crucial for the adoption of deep learning systems to safety-critical applications. Uncertainty estimates can be used as a failure signal, which is necessary for automating complex tasks where safety is a concern. Furthermore, current deep learning systems do not provide uncertainty estimates,...
Resource Type:: Dissertation

Efficient Algorithms for Robust Spatiotemporal Data Analysis

Creator:: Moore, Travis W.
Abstract:: Many large-scale data analysis applications involve data that can vary over both time and space. Often the primary goal of analyzing spatiotemporal data is identifying trends, movements, and sudden changes with respect to time, location, or both. This can include a variety of applications in economics (housing prices, unemployment, job...
Resource Type:: Dissertation

Theory and Implementation of a Variational Database Management System

Creator:: Ataei, Parisa S.
Abstract:: In this thesis, I present the variational database management system, a formal framework and its implementation for representing variation in relational databases and managing variational information needs. A variational database is intended to support any kind of variation in a database. Specific kinds of variation in databases have already been...
Resource Type:: Dissertation

ScholarsArchive@OSU

Semantic embodied navigation : developing agents that navigate from language and vision

Automatic Explanations of Computation Results with Value Decompositions and Dominating Sets

Characterizing and Addressing Dataset Shift with Deep Learning

Generative Models Meet Explainable AI and Long-Tail Learning: from Attribution Maps to Image Synthesis

Agile Bipedal Locomotion via Hierarchical Control by Incorporating Physical Principles, Learning, and Optimization

Deep Learning for Human and Biological Languages

Deep Convolutional Network on Point Clouds for 3D Scene Understanding

Uncertainty in Deep Learning with Implicit Neural Networks

Efficient Algorithms for Robust Spatiotemporal Data Analysis

Theory and Implementation of a Variational Database Management System

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