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2. Abstractions for Probabilistic Programming to Support Model Development
3. AI and the Writer: How Language Models Support Creative Writers
4. Algorithm-Hardware Co-design for Ultra-Low-Power Machine Learning and Neuromorphic Computing
5. Computational Models of Argument Structure and Argument Quality for Understanding Misinformation
6. Designing Exploratory Search Systems that Stimulate Memory and Reduce Cognitive Load
7. Interpretable Machine Learning for the Social Sciences: Applications in Political Science and Labor Economics
8. Machine Learning Framework for Causal Modeling for Process Fault Diagnosis and Mechanistic Explanation Generation
9. Multimodal deep learning systems for analysis of human behavior, preference, and state
10. Robust Machine Learning by Integrating Context
11. "Seeing Red" or "Tickled Pink"? Investigating the Power of Language and Vision Models through Color, Emotion, and Metaphor
12. Task-dependent representations for cerebellar learning
13. Toward Annotation Efficiency in Biased Learning Settings for Natural Language Processing
14. Towards Causal Reinforcement Learning
15. Ultra-low-power Audio Feature Extraction using Time-Mode Analog Signal Processing Circuits
16. Artificial Intelligence for Detection, Characterization, and Classification of Complex Visual Patterns in Medical Imaging; Applications in Pulmonary and Neuro-imaging
17. Beyond Worst-Case Analysis of Optimization in the Era of Machine Learning
18. Deep Self-Modeling for Robotic Systems
19. Efficient Machine Teaching Frameworks for Natural Language Processing
20. Fusing simultaneously acquired EEG-fMRI using deep learning
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