Trustworthy Deep Learning

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Index Papers Our Slides
1 BIAS ALSO MATTERS: BIAS ATTRIBUTION FOR DEEP NEURAL NETWORK EXPLANATION Arsh Survey
2 Data Shapley: Equitable Valuation of Data for Machine Learning Arsh Survey
  What is your data worth? Equitable Valuation of Data Sanchit Survey
3 Neural Network Attributions: A Causal Perspective Zhe Survey
4 Defending Against Neural Fake News Eli Survey
5 Interpretation of Neural Networks is Fragile Eli Survey
  Interpretation of Neural Networks is Fragile Pan Survey
6 Parsimonious Black-Box Adversarial Attacks Via Efficient Combinatorial Optimization Eli Survey
7 Retrofitting Word Vectors to Semantic Lexicons Morris Survey
8 On Evaluation of Adversarial Perturbations for Sequence-to-Sequence Models Morris Survey
9 Towards Deep Learning Models Resistant to Adversarial Attacks Pan Survey
10 Robust Attribution Regularization Pan Survey
11 Sanity Checks for Saliency Maps Sanchit Survey
12 Survey of data generation and evaluation in Interpreting DNN pipelines Sanchit Survey
13 Think Architecture First: Benchmarking Deep Learning Interpretability in Time Series Predictions Sanchit Survey
14 Universal Adversarial Triggers for Attacking and Analyzing NLP Sanchit Survey
15 Apricot: Submodular selection for data summarization in Python Arsh Survey