2024
Robust Algorithmic Recourse Under Model Multiplicity With Probabilistic Guarantees.
IEEE J. Sel. Areas Inf. Theory, 2024
Interpreting Language Reward Models via Contrastive Explanations.
CoRR, 2024
Global Graph Counterfactual Explanation: A Subgraph Mapping Approach.
CoRR, 2024
Quantifying Prediction Consistency Under Model Multiplicity in Tabular LLMs.
CoRR, 2024
Cross-Domain Graph Data Scaling: A Showcase with Diffusion Models.
CoRR, 2024
IKEA Manuals at Work: 4D Grounding of Assembly Instructions on Internet Videos.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
Sequential Harmful Shift Detection Without Labels.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
Progressive Inference: Explaining Decoder-Only Sequence Classification Models Using Intermediate Predictions.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
Counterfactual Metarules for Local and Global Recourse.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
PICE: Polyhedral Complex Informed Counterfactual Explanations.
Proceedings of the Seventh AAAI/ACM Conference on AI, Ethics, and Society (AIES-24) - Full Archival Papers, October 21-23, 2024, San Jose, California, USA, 2024
2023
GLOBE-CE: A Translation Based Approach for Global Counterfactual Explanations.
Proceedings of the International Conference on Machine Learning, 2023
Robust Counterfactual Explanations for Neural Networks With Probabilistic Guarantees.
Proceedings of the International Conference on Machine Learning, 2023
On the Connection between Game-Theoretic Feature Attributions and Counterfactual Explanations.
Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 2023
Symbolic Metamodels for Interpreting Black-Boxes Using Primitive Functions.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023
2022
Global Counterfactual Explanations: Investigations, Implementations and Improvements.
CoRR, 2022
CLEAR: Generative Counterfactual Explanations on Graphs.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Robust Counterfactual Explanations for Tree-Based Ensembles.
Proceedings of the International Conference on Machine Learning, 2022
2021
A Survey on the Robustness of Feature Importance and Counterfactual Explanations.
CoRR, 2021
2020
Reliable Local Explanations for Machine Listening.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020
2019
GAN-based Generation and Automatic Selection of Explanations for Neural Networks.
CoRR, 2019
Atrial Fibrillation Stratification Via Super-Resolution Analysis of Fibrillatory Waves.
Proceedings of the 46th Computing in Cardiology, 2019
2018
A Method for Chaotic Self-Modulation in Nonlinear Colpitts Oscillator and its Potential Applications.
Circuits Syst. Signal Process., 2018
A Study On Convolutional Neural Network Based End-To-End Replay Anti-Spoofing.
CoRR, 2018
Analysing The Predictions Of a CNN-Based Replay Spoofing Detection System.
Proceedings of the 2018 IEEE Spoken Language Technology Workshop, 2018
Understanding a Deep Machine Listening Model Through Feature Inversion.
Proceedings of the 19th International Society for Music Information Retrieval Conference, 2018
"What are You Listening to?" Explaining Predictions of Deep Machine Listening Systems.
Proceedings of the 26th European Signal Processing Conference, 2018
2017
Local Interpretable Model-Agnostic Explanations for Music Content Analysis.
Proceedings of the 18th International Society for Music Information Retrieval Conference, 2017