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1
Safety, Robustness, and Interpretability in Machine Learning
Safety, Robustness, and Interpretability in Machine Learning
Pfrommer, Samuel Ian. | University of California, Berkeley | 2025
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2
Robust Inference and Interpretability in Complex Statistical Models: From Model Distillation to Targeted Learning
Robust Inference and Interpretability in Complex Statistical Models: From Model Distillation to Targeted Learning
Zhou, Yunzhe. | University of California, Berkeley | 2025
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3
Interpreting the Inner-Workings of Vision Models
Interpreting the Inner-Workings of Vision Models
Gandelsman, Yossi. | University of California, Berkeley | 2025
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4
Between Pixels and Policies: Toward Interpretable Representations for (Inter)Action
Between Pixels and Policies: Toward Interpretable Representations for (Inter)Action
Stocking, Kaylene Caswell. | University of California, Berkeley | 2025
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5
Science of Deep Learning: From Initialization to Emergent Structures
Science of Deep Learning: From Initialization to Emergent Structures
Doshi, Darshil. | University of Maryland, College Park | 2025
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6
Human-AI Interaction in the Era of Large Language Models (LLMs)
Human-AI Interaction in the Era of Large Language Models (LLMs)
Mohammadi, Behnam. | Carnegie Mellon University | 2025
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7
Interpretable, Robust, and Controllable Machine Learning Methods for Medical Imaging
Interpretable, Robust, and Controllable Machine Learning Methods for Medical Imaging
Wang, Alan. | Cornell University | 2024
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8
Building Features in Visual Neural Networks
Building Features in Visual Neural Networks
Hamblin, Christopher. | Harvard University | 2024
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9
Transparent Machine Learning: Theory and Computation- [electronic resource]
Transparent Machine Learning: Theory and Computation- [electronic resource]
Covert, Ian C.Computer Science and Engineering. | University of Washington. | 2023
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10
Interpretable Machine Learning Architectures for Efficient Signal Detection with Applications to Gravitational Wave Astronomy- [electronic resource]
Interpretable Machine Learning Architectures for Efficient Signal Detection with Applications to Gravitational Wave Astronomy- [electronic resource]
Yan, Jingkai.Electrical Engineering. | Columbia University. | 2024
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