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Filtering by: Advisor Li, Fuxin Remove constraint Advisor: Li, Fuxin Committee Member Fern, Alan Remove constraint Committee Member: Fern, Alan Rights Statement In Copyright Remove constraint Rights Statement: In Copyright

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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
Detecting Anomalies in Object Appearance and Motion Dynamics

Creator:

Alotaibi, Mazen

Abstract:

Machine common sense remains a broad, potentially unbounded problem in AI. Our focus is to move toward AI systems that can develop common-sense reasoning similar to humans to detect anomalies. In particular, we study the problem of detecting the violation of expectations when object appearance or motion dynamics change from...

Resource Type:

Capstone Project
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
Toward Disentangling the Activations of the Deep Networks via Low-dimensional Embedding and Non-negative Factorization

Creator:

Khorram, Saeed

Abstract:

In this thesis, we introduce a novel Explanation Neural Network (XNN) to explain the predictions made by a deep network. The XNN works by embedding a high-dimensional activation vector of a deep network layer non-linearly into a low-dimensional explanation space while retaining faithfulness i.e., the original deep learning predictions can...

Resource Type:

Masters Thesis
Methods for Detection and Recovery of Out-of-Distribution Examples

Creator:

Ratzlaff, Neale J.

Abstract:

Deep neural networks currently comprise the backbone of many applications where safety is a critical concern, for example: autonomous driving and medical diagnostics. Unfortunately these systems currently fail to detect out-of-distribution (OOD) inputs and can be prone to making dangerous errors when exposed to them. In addition, these same systems...

Resource Type:

Masters Thesis
Open Set Learning with Counterfactual Images

Creator:

Neal, Lawrence W.

Abstract:

In open set recognition, a classifier must label instances of known classes while detecting instances of unknown classes not encountered during training. To detect unknown classes while still generalizing to new instances of existing classes, this thesis introduces a dataset augmentation technique called counterfactual image generation. This approach, based on...

Resource Type:

Masters Thesis

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Academic Affiliation

Electrical Engineering and Computer Science7

Advisor

Li, Fuxin[remove]7
Fern, Xiaoli Z.1

Commencement Year

Commencement Year range begin – Commencement Year range end

Current results range from 2019 to 2023

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Committee Member

Fern, Alan[remove]7
Wong, Weng-Keen3
Dietterich, Tom2
Hollinger, Geoff2
Todorovic, Sinisa2
more Committee Members »

Creator

Khorram, Saeed2
Alotaibi, Mazen1
Neal, Lawrence W.1
Ratzlaff, Neale1
Ratzlaff, Neale J.1
more Creators »

Contributor

Li, Fuxin2
Fern, Alan1
Fu, Xiao1
Irvine, Jed1
Kim, Chanho1
more Contributors »

Date

Date range begin – Date range end

Current results range from 2018 to 2023

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Decade

2020-20295
2010-20192

Degree Field

Computer Science6
Artificial Intelligence1

Degree Level

Master's4
Doctoral3

Degree Name

Master of Science (M.S.)4
Doctor of Philosophy (Ph.D.)3

Language

English [eng]7

License

All rights reserved6

Peer Reviewed

No7

Resource Type

Dissertation3
Masters Thesis3
Capstone Project1

Rights Statement

In Copyright[remove]7

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