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We believe that collaborative discussion leads to more concrete understanding of the complexities of AI/ML models. Every other Friday, we get together to discuss the details of an impactful paper in the field to break down the intricacies of the contribution and further out understanding. We open these discussion to any researcher that is interested in getting involved and encourage you to attend!
November 10, 2025 - MRI Harmonization andΒ Domain Genearlization
π Lead by Savannah Hays (Guest speaker; Johns Hopkins Univeristy)
π’ AER 356
π 1:30 - 2:20 pm
September, 2025 - Show and Tell: Visually Explainable Deep Neural Nets via Spatially-Aware Concept Bottleneck Models
π Lead by Ahsan Akash Habib
π’ AER 321
π 9-10am
August, 2025 - CONFINE: Conformal Prediction for Interpretable Neural Networks
π Lead by Rizwan Ahmad
π’ AER 321
π 9-10am
February 26, 2025 - Mitigating Neural Network Overconfidence with Logit Normalization
π Lead by Jacob Thrasher
π’ AER 321
π 9-10am
February 14, 2025 - Generative Modeling by Estimating Gradients of the Data Distribution
π Lead by Abid Rahman
π’ AER 321
π 12-1pm
February 6, 2024 - Large Language Models Cannot Self-Correct Reasoning Yet
π Lead by Greg Murray
π’ AER 356
π 11am
October 18, 2024 - Epistemic Uncertainty Quantification for Pre-trained Neural Networks
π Lead by Alina Devkota
π’ AER 356
π 9-10am
October 4, 2024 - Evaluating Bias and Fairness in Gender-Neutral Pretrained Vision-and-Language Models
π Lead by Greg Murray
π’ AER 356
π 9-10am
September 20, 2024 - Attention is all you need
π Lead by Nima Najafzadeh
π’ AER 356
π 9-10am
September 06, 2024 - An Overview of Diffusion models: Applications, Guided Generation, Statistical Rates and Optimization
π Lead by Shivam
π’ AER 356
π 9-10am
August 23, 2024 - Class Anchor Clustering: A Loss for Distance-based Open Set Recognition
π Lead by Jacob Thrasher
π’ AER 356
π 9-10am
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