David Alvarez-Melis

According to our database, David Alvarez-Melis authored at least 25 papers between 2015 and 2022.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2022

Why GANs are overkill for NLP.

David Alvarez-Melis, Vikas K. Garg, Adam Tauman Kalai

CoRR, 2022

Hierarchical Optimal Transport for Comparing Histopathology Datasets.

Anna Yeaton, Rahul G. Krishnan, Rebecca J. Mieloszyk, David Alvarez-Melis, Grace Huynh

CoRR, 2022

2021

Optimizing Functionals on the Space of Probabilities with Input Convex Neural Networks.

David Alvarez-Melis, Yair Schiff, Youssef Mroueh

CoRR, 2021

A Human-Centered Interpretability Framework Based on Weight of Evidence.

David Alvarez-Melis, Harmanpreet Kaur, Hal Daumé III, Hanna M. Wallach, Jennifer Wortman Vaughan

CoRR, 2021

Dataset Dynamics via Gradient Flows in Probability Space.

David Alvarez-Melis, Nicolò Fusi

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Gradient Flows in Dataset Space.

David Alvarez-Melis, Nicolò Fusi

CoRR, 2020

Geometric Dataset Distances via Optimal Transport.

David Alvarez-Melis, Nicolò Fusi

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Unsupervised Hierarchy Matching with Optimal Transport over Hyperbolic Spaces.

David Alvarez-Melis, Youssef Mroueh, Tommi S. Jaakkola

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Probabilistic Bias Mitigation in Word Embeddings.

Hailey James-Sorenson, David Alvarez-Melis

CoRR, 2019

Weight of Evidence as a Basis for Human-Oriented Explanations.

David Alvarez-Melis, Hal Daumé III, Jennifer Wortman Vaughan, Hanna M. Wallach

CoRR, 2019

Functional Transparency for Structured Data: a Game-Theoretic Approach.

Guang-He Lee, Wengong Jin, David Alvarez-Melis, Tommi S. Jaakkola

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

Learning Generative Models across Incomparable Spaces.

Charlotte Bunne, David Alvarez-Melis, Andreas Krause, Stefanie Jegelka

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

Towards Robust, Locally Linear Deep Networks.

Guang-He Lee, David Alvarez-Melis, Tommi S. Jaakkola

Proceedings of the 7th International Conference on Learning Representations, 2019

Towards Optimal Transport with Global Invariances.

David Alvarez-Melis, Stefanie Jegelka, Tommi S. Jaakkola

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Game-Theoretic Interpretability for Temporal Modeling.

Guang-He Lee, David Alvarez-Melis, Tommi S. Jaakkola

CoRR, 2018

On the Robustness of Interpretability Methods.

David Alvarez-Melis, Tommi S. Jaakkola

CoRR, 2018

Towards Robust Interpretability with Self-Explaining Neural Networks.

David Alvarez-Melis, Tommi S. Jaakkola

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Distributional Adversarial Networks.

Chengtao Li, David Alvarez-Melis, Keyulu Xu, Stefanie Jegelka, Suvrit Sra

Proceedings of the 6th International Conference on Learning Representations, 2018

Gromov-Wasserstein Alignment of Word Embedding Spaces.

David Alvarez-Melis, Tommi S. Jaakkola

Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

Structured Optimal Transport.

David Alvarez-Melis, Tommi S. Jaakkola, Stefanie Jegelka

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

Tree-structured decoding with doubly-recurrent neural networks.

David Alvarez-Melis, Tommi S. Jaakkola

Proceedings of the 5th International Conference on Learning Representations, 2017

A causal framework for explaining the predictions of black-box sequence-to-sequence models.

David Alvarez-Melis, Tommi S. Jaakkola

Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2017

2016

Word Embeddings as Metric Recovery in Semantic Spaces.

Tatsunori B. Hashimoto, David Alvarez-Melis, Tommi S. Jaakkola

Trans. Assoc. Comput. Linguistics, 2016

Topic Modeling in Twitter: Aggregating Tweets by Conversations.

David Alvarez-Melis, Martin Saveski

Proceedings of the Tenth International Conference on Web and Social Media, 2016

2015

Word, graph and manifold embedding from Markov processes.

Tatsunori B. Hashimoto, David Alvarez-Melis, Tommi S. Jaakkola

CoRR, 2015