CS 6463 Advanced Topics: Trust in AI

Instructor: Sumit Kumar Jha

Optional Meeting: Friday 3:30 pm @ Zoom

Online Asynchronous Course Schedule

 

Part I: Explainable Artificial Intelligence

Week 1-2 (Jan 17 to Jan 27): Deep Inside Convolutional Networks: Visualizing Image Classification Models and Saliency Maps https://arxiv.org/pdf/1312.6034.pdf

Lecture and Related Materials

Week 3 (Jan 30 to Feb 3): Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization https://arxiv.org/pdf/1610.02391.pdf

Lecture and Related Materials

Week 4 (Feb 6 to Feb 10): Axiomatic Attribution for Deep Networks (Integrated Gradients) http://proceedings.mlr.press/v70/sundararajan17a/sundararajan17a.pdf

Lecture and Related Materials

Week 5 (Feb 13 to Feb 17): SmoothGrad: removing noise by adding noise https://arxiv.org/pdf/1706.03825.pdf

Lecture and Related Materials

Week 6 (Feb 20 to Feb 24): Fast Axiomatic Attribution for Neural Networks https://arxiv.org/pdf/2111.07668.pdf

Lecture and Related Materials

Week 7: (Feb 27 to March 3) Self-Attention Attribution: Interpreting Information Interactions Inside Transformer https://arxiv.org/abs/2004.11207

Lecture and Related Materials

 

 

Part II: Confidence Metrics for Neural Networks

Week 8 (March 6 to March 10) : Probabilistic Outputs for Support Vector Machines and Comparisons to Regularized Likelihood Methods https://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.41.1639

Lecture and Related Materials

Week 9: Spring Break

Week 10 (March 20 to March 24): On calibration of modern neural networks https://proceedings.mlr.press/v70/guo17a/guo17a.pdf

Lecture and Related Materials

Week 11 (March 27 to 31): Attribution-Based Confidence Metric For Deep Neural Networks

https://proceedings.neurips.cc/paper/2019/file/bc1ad6e8f86c42a371aff945535baebb-Paper.pdf

Lecture and Related Materials

 

Part III: NeuroSymbolic AI

Week: D-CODE: Discovering Closed-form ODEs from Observed Trajectories https://openreview.net/forum?id=wENMvIsxNN

Lecture and Related Materials

 

 

Part IV: Large Visual and Language Models

 

 

Week 12 (April 3 to 7): TBD

Week 13 (April 10 to 14): TBD

Week 14 (April 17 to 21): TBD

Week 15 (April 24 to 28): TBD

Week 16 (May 1 to 2): In-class Project (optional) Presentations (videos available on UTSA Blackboard/Canvas).

May 2, 2023: Last Day of Classes