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Filtering by: Alternative title ssim 95-80-01 Committee Member Fern, Alan Creator Khorram, Saeed

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

Full Text:

perfor- mance in many domains such as computer vision [40, 80, 39]. On the whole, they process data by
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

Full Text:

. . . . . . . . . . . . . . . . . . . . . . . . . . . 95 6.4 Ablation Study. In this table, we provide the quantitative results obtained from the