Browsing MIT Libraries by Title
Now showing items 5059-5078 of 61744
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Bayesian Linear Modeling in High Dimensions: Advances in Hierarchical Modeling, Inference, and Evaluation
(Massachusetts Institute of Technology, 2022-05)Across the sciences, social sciences and engineering, applied statisticians seek to build understandings of complex relationships from increasingly large datasets. In statistical genetics, for example, we observe up to ... -
Bayesian modeling of manner and path psychological data
(Massachusetts Institute of Technology, 2004)How people and computers can learn the meaning of words has long been a key question for both AI and cognitive science. It is hypothesized that a person acquires a bias to favor the characteristics of their native language, ... -
Bayesian modeling of microwave foregrounds
(Massachusetts Institute of Technology, 2008)In the past decade, advances in precision cosmology have pushed our understanding of the evolving Universe to new limits. Since the discovery of the cosmic microwave background (CMB) radiation in 1965 by Penzias and Wilson, ... -
Bayesian models for screening and diagnosis of pulmonary disease
(Massachusetts Institute of Technology, 2018)Pulmonary and respiratory diseases comprise a large proportion of the global disease burden, responsible for both mortality and disability, with the most common ailments being asthma, chronic obstructive pulmonary disorder ... -
Bayesian models for visual information retrieval
(Massachusetts Institute of Technology, 2000)This thesis presents a unified solution to visual recognition and learning in the context of visual information retrieval. Realizing that the design of an effective recognition architecture requires careful consideration ... -
Bayesian motion estimation and segmentation
(Massachusetts Institute of Technology, 1998)Estimating motion in scenes containing multiple moving objects remains a difficult problem in computer vision yet is solved effortlessly by humans. In this thesis we present a computational investigation of this astonishing ... -
Bayesian network models of biological signaling pathways
(Massachusetts Institute of Technology, 2006)Cells communicate with other cells, and process cues from their environment, via signaling pathways, in which extracellular cues trigger a cascade of information flow, causing signaling molecules to become chemically, ... -
Bayesian networks for cardiovascular monitoring
(Massachusetts Institute of Technology, 2006)In the Intensive Care Unit, physicians have access to many types of information when treating patients. Physicians attempt to consider as much of the relevant information as possible, but the astronomically large amounts ... -
Bayesian nonparametric approaches for reinforcement learning in partially observable domains
(Massachusetts Institute of Technology, 2012)Making intelligent decisions from incomplete information is critical in many applications: for example, medical decisions must often be made based on a few vital signs, without full knowledge of a patient's condition, and ... -
Bayesian nonparametric learning of complex dynamical phenomena
(Massachusetts Institute of Technology, 2009)The complexity of many dynamical phenomena precludes the use of linear models for which exact analytic techniques are available. However, inference on standard nonlinear models quickly becomes intractable. In some cases, ... -
Bayesian nonparametric learning with semi-Markovian dynamics
(Massachusetts Institute of Technology, 2010)There is much interest in the Hierarchical Dirichlet Process Hidden Markov Model (HDP-HMM) as a natural Bayesian nonparametric extension of the ubiquitous Hidden Markov Model for learning from sequential and time-series ... -
Bayesian nonparametric reward learning from demonstration
(Massachusetts Institute of Technology, 2013)Learning from demonstration provides an attractive solution to the problem of teaching autonomous systems how to perform complex tasks. Demonstration opens autonomy development to non-experts and is an intuitive means of ... -
Bayesian optimization and Cartesian-grid simulations for artificial reef design
(Massachusetts Institute of Technology, 2023-06)Coastal erosion threatens communities close to the shore worldwide, and it has become a significant concern in recent years due to increased sea levels and storm frequency driven by global warming. In the search for ... -
Bayesian optimization as a probabilistic meta-program
(Massachusetts Institute of Technology, 2015)This thesis answers two questions: 1. How should probabilistic programming languages in- corporate Gaussian processes? and 2. Is it possible to write a probabilistic meta-program for Bayesian optimization, a probabilistic ... -
Bayesian population inference for effective connectivity
(Massachusetts Institute of Technology, 2005)A hierarchical model based on the Multivariate Autoregessive (MAR) process is proposed to jointly model functional neuroimaging time series collected from multiple subjects, and to characterize the distribution of MAR ... -
Bayesian scene understanding with object-based latent representation and multi-modal sensor fusion
(Massachusetts Institute of Technology, 2021)Scene understanding systems transform observations of an environment into a representation that facilitates reasoning over that environment. In this context, many reasoning tasks benefit from a high-level, object-based ... -
Bayesian Theory of Mind : modeling human reasoning about beliefs, desires, goals, and social relations
(Massachusetts Institute of Technology, 2012)This thesis proposes a computational framework for understanding human Theory of Mind (ToM): our conception of others' mental states, how they relate to the world, and how they cause behavior. Humans use ToM to predict ... -
A Bayesian theory of mind approach to nonverbal communication for human-robot interactions : a computational formulation of intentional inference and belief manipulation
(Massachusetts Institute of Technology, 2017)Much of human social communication is channeled through our facial expressions, body language, gaze directions, and many other nonverbal behaviors. A robot's ability to express and recognize the emotional states of people ... -
Bayesian time series models and scalable inference
(Massachusetts Institute of Technology, 2014)With large and growing datasets and complex models, there is an increasing need for scalable Bayesian inference. We describe two lines of work to address this need. In the first part, we develop new algorithms for inference ... -
Bayesian Time Series Structure Learning: Formulation of an Event Driven Prior Distribution
(Massachusetts Institute of Technology, 2023-06)We study the prior distribution over structures of a Bayesian time series structure learning model—the Temporal Interaction Model (TIM) of Siracusa and Fisher III. We develop a new method for setting the hyperparameters ...
