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Poster
Mon 1:00 Rethinking the Role of Gradient-based Attribution Methods for Model Interpretability
Suraj Srinivas, François Fleuret
Oral
Mon 5:30 Rethinking the Role of Gradient-based Attribution Methods for Model Interpretability
Suraj Srinivas, François Fleuret
Poster
Mon 9:00 Learning explanations that are hard to vary
Giambattista Parascandolo, Alexander Neitz, Antonio Orvieto, Luigi Gresele, Bernhard Schoelkopf
Poster
Mon 9:00 Learning "What-if" Explanations for Sequential Decision-Making
Ioana Bica, Dan Jarrett, Alihan Hüyük, Mihaela van der Schaar
Poster
Mon 9:00 On the Stability of Fine-tuning BERT: Misconceptions, Explanations, and Strong Baselines
Marius Mosbach, Maksym Andriushchenko, Dietrich Klakow
Poster
Mon 9:00 Shapley Explanation Networks
Rui Wang, Xiaoqian Wang, David Inouye
Poster
Mon 9:00 Shapley explainability on the data manifold
Christopher Frye, Damien De Mijolla, Tom Begley, Laurence Cowton, Megan Stanley, Ilya Feige
Poster
Mon 17:00 Remembering for the Right Reasons: Explanations Reduce Catastrophic Forgetting
Sayna Ebrahimi, Suzanne Petryk, Akash Gokul, William Gan, Joseph E Gonzalez, Marcus Rohrbach, trevor darrell
Oral
Mon 19:15 Contrastive Explanations for Reinforcement Learning via Embedded Self Predictions
Zhengxian Lin, Kin-Ho Lam, Alan Fern
Poster
Tue 9:00 Getting a CLUE: A Method for Explaining Uncertainty Estimates
Javier Antorán, Umang Bhatt, Tameem Adel, Adrian Weller, José Miguel Hernández Lobato
Poster
Tue 17:00 RNNLogic: Learning Logic Rules for Reasoning on Knowledge Graphs
Meng Qu, Junkun Chen, Louis-Pascal A Xhonneux, Yoshua Bengio, Jian Tang
Poster
Tue 17:00 Debiasing Concept-based Explanations with Causal Analysis
Taha Bahadori, David Heckerman
Poster
Wed 1:00 Explainable Deep One-Class Classification
Philipp Liznerski, Lukas Ruff, Robert A Vandermeulen, Billy J Franks, Marius Kloft, Klaus R Muller
Oral
Wed 4:05 Getting a CLUE: A Method for Explaining Uncertainty Estimates
Javier Antorán, Umang Bhatt, Tameem Adel, Adrian Weller, José Miguel Hernández Lobato
Poster
Wed 17:00 Learning to Deceive Knowledge Graph Augmented Models via Targeted Perturbation
Mrigank Raman, Aaron Chan, Siddhant Agarwal, PeiFeng Wang, Hansen Wang, Sungchul Kim, Ryan Rossi, Handong Zhao, Nedim Lipka, Xiang Ren
Poster
Wed 17:00 Learning and Evaluating Representations for Deep One-Class Classification
Kihyuk Sohn, Chun-Liang Li, Jinsung Yoon, Minho Jin, Tomas Pfister
Poster
Wed 17:00 Evaluations and Methods for Explanation through Robustness Analysis
Cheng-Yu Hsieh, Chih-Kuan Yeh, Xuanqing Liu, Pradeep K Ravikumar, Seungyeon Kim, Sanjiv Kumar, Cho-Jui Hsieh
Poster
Thu 1:00 Contrastive Explanations for Reinforcement Learning via Embedded Self Predictions
Zhengxian Lin, Kin-Ho Lam, Alan Fern
Poster
Thu 17:00 A Learning Theoretic Perspective on Local Explainability
Jeffrey Li, Vaishnavh Nagarajan, Gregory Plumb, Ameet Talwalkar
Poster
Thu 17:00 Evaluation of Similarity-based Explanations
Kazuaki Hanawa, Sho Yokoi, Satoshi Hara, Kentaro Inui
Workshop
Fri 11:00 Poster session on GatherTown (see link above): all papers ("orals" and "posters") --- links to papers : see Workshop Website
Workshop
$\delta$-CLUE: Diverse Sets of Explanations for Uncertainty Estimates
Dan Ley, Umang Bhatt, Adrian Weller