David Alvarez-Melis

CoRR, 2024

Strongly Isomorphic Neural Optimal Transport Across Incomparable Spaces.

[BibT_eX]

[DOI]

Athina Sotiropoulou

CoRR, 2024

CharED: Character-wise Ensemble Decoding for Large Language Models.

[BibT_eX]

[DOI]

CoRR, 2024

A Label is Worth a Thousand Images in Dataset Distillation.

[BibT_eX]

[DOI]

Tian Qin

Zhiwei Deng

CoRR, 2024

Continuous Language Model Interpolation for Dynamic and Controllable Text Generation.

[BibT_eX]

[DOI]

Sara Kangaslahti

CoRR, 2024

Distributional Dataset Distillation with Subtask Decomposition.

[BibT_eX]

[DOI]

Tian Qin

Zhiwei Deng

CoRR, 2024

Tag-LLM: Repurposing General-Purpose LLMs for Specialized Domains.

[BibT_eX]

[DOI]

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

2023

Generating Synthetic Datasets by Interpolating along Generalized Geodesics.

[BibT_eX]

[DOI]

Jiaojiao Fan

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Domain adaptation using optimal transport for invariant learning using histopathology datasets.

[BibT_eX]

[DOI]

Kianoush Falahkheirkhah

Alex Xijie Lu

Grace Huynh

Proceedings of the Medical Imaging with Deep Learning, 2023

InfoOT: Information Maximizing Optimal Transport.

[BibT_eX]

[DOI]

Ching-Yao Chuang

Stefanie Jegelka

Proceedings of the International Conference on Machine Learning, 2023

2022

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

[BibT_eX]

[DOI]

Jacobo Sarabia del Castillo

Yair Schiff

Youssef Mroueh

Trans. Mach. Learn. Res., 2022

Transfer RL via the Undo Maps Formalism.

[BibT_eX]

[DOI]

CoRR, 2022

Budget-Constrained Bounds for Mini-Batch Estimation of Optimal Transport.

[BibT_eX]

[DOI]

CoRR, 2022

Neural Unbalanced Optimal Transport via Cycle-Consistent Semi-Couplings.

[BibT_eX]

[DOI]

Frederike Lübeck

Charlotte Bunne

Gabriele Gut

Lucas Pelkmans

CoRR, 2022

Interpretable Distribution Shift Detection using Optimal Transport.

[BibT_eX]

[DOI]

Neha Hulkund

CoRR, 2022

Why GANs are overkill for NLP.

[BibT_eX]

[DOI]

Vikas Garg

Adam Tauman Kalai

CoRR, 2022

Are GANs overkill for NLP?

[BibT_eX]

[DOI]

Vikas Garg

Adam Kalai

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Hierarchical Optimal Transport for Comparing Histopathology Datasets.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Medical Imaging with Deep Learning, 2022

2021

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

[BibT_eX]

[DOI]

CoRR, 2021

Dataset Dynamics via Gradient Flows in Probability Space.

[BibT_eX]

[DOI]

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

From Human Explanation to Model Interpretability: A Framework Based on Weight of Evidence.

[BibT_eX]

[DOI]

Proceedings of the Ninth AAAI Conference on Human Computation and Crowdsourcing, 2021

2020

Gradient Flows in Dataset Space.

[BibT_eX]

[DOI]

CoRR, 2020

Geometric Dataset Distances via Optimal Transport.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Youssef Mroueh

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

2019

Probabilistic Bias Mitigation in Word Embeddings.

[BibT_eX]

[DOI]

Hailey James-Sorenson

CoRR, 2019

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

[BibT_eX]

[DOI]

Hal Daumé III

Hanna M. Wallach

CoRR, 2019

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

[BibT_eX]

[DOI]

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

Learning Generative Models across Incomparable Spaces.

[BibT_eX]

[DOI]

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

Towards Robust, Locally Linear Deep Networks.

[BibT_eX]

[DOI]

Guang-He Lee

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

Towards Optimal Transport with Global Invariances.

[BibT_eX]

[DOI]

Stefanie Jegelka

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

2018

Game-Theoretic Interpretability for Temporal Modeling.

[BibT_eX]

[DOI]

Guang-He Lee

CoRR, 2018

On the Robustness of Interpretability Methods.

[BibT_eX]

[DOI]

CoRR, 2018

Towards Robust Interpretability with Self-Explaining Neural Networks.

[BibT_eX]

[DOI]

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

Distributional Adversarial Networks.

[BibT_eX]

[DOI]

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

Gromov-Wasserstein Alignment of Word Embedding Spaces.

[BibT_eX]

[DOI]

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

Structured Optimal Transport.

[BibT_eX]

[DOI]

Stefanie Jegelka

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

2017

Tree-structured decoding with doubly-recurrent neural networks.

[BibT_eX]

[DOI]

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

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

[BibT_eX]

[DOI]

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

2016

Word Embeddings as Metric Recovery in Semantic Spaces.

[BibT_eX]

[DOI]

Tatsunori B. Hashimoto

Trans. Assoc. Comput. Linguistics, 2016

Topic Modeling in Twitter: Aggregating Tweets by Conversations.

[BibT_eX]

[DOI]

Martin Saveski

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

2015

Word, graph and manifold embedding from Markov processes.

[BibT_eX]

[DOI]

Tatsunori B. Hashimoto