Aditya Chattopadhyay

Benjamin David Haeffele

Donald Geman

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Bootstrapping Variational Information Pursuit with Large Language and Vision Models for Interpretable Image Classification.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Interpretable by Design: Learning Predictors by Composing Interpretable Queries.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., June, 2023

Learning Interpretable Queries for Explainable Image Classification with Information Pursuit.

[BibT_eX]

[DOI]

Stefan Kolek

Héctor Andrade-Loarca

Gitta Kutyniok

CoRR, 2023

Variational Information Pursuit with Large Language and Multimodal Models for Interpretable Predictions.

[BibT_eX]

[DOI]

Benjamin David Haeffele

CoRR, 2023

Learning Graph Variational Autoencoders with Constraints and Structured Priors for Conditional Indoor 3D Scene Generation.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2023

Information Maximization Perspective of Orthogonal Matching Pursuit with Applications to Explainable AI.

[BibT_eX]

[DOI]

Ryan Pilgrim

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Variational Information Pursuit for Interpretable Predictions.

[BibT_eX]

[DOI]

Benjamin David Haeffele

Donald Geman

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Structured Graph Variational Autoencoders for Indoor Furniture layout Generation.

[BibT_eX]

[DOI]

CoRR, 2022

2019

Neural Network Attributions: A Causal Perspective.

[BibT_eX]

[DOI]

Vineeth N. Balasubramanian

Piyushi Manupriya

Anirban Sarkar

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Grad-CAM++: Generalized Gradient-Based Visual Explanations for Deep Convolutional Networks.

[BibT_eX]

[DOI]