David Alvarez-Melis
23 papers · 2017–2025 · 7 conferences · across top CS/AI conferences
Achievements
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🌍 Conference Polyglot (7) 🌉 Interdisciplinary Bridge 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🏃 Academic Marathon (8)
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Interdisciplinary Bridge
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Conference Polyglot
(7)
🏃
Academic Marathon
(8)
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Keyword Collector
(84)
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Prolific Year
(5)
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Century Club
(23)
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Unstoppable
(9)
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❓
The Questioner
(2)
Conferences
ICML (5)
AISTATS (4)
EMNLP (4)
NIPS (4)
ICLR (2)
MIDL (2)
UAI (2)
Top co-authors
Research topics
Keywords
optimal transport
(8)
domain adaptation
(5)
transfer learning
(3)
representation learning
(3)
generative adversarial network
(2)
word embedding
(2)
gromov-wasserstein distance
(2)
dataset distance
(2)
cross-lingual transfer
(1)
kl divergence
(1)
mathematical reasoning
(1)
natural language processing
(1)
manifold learning
(1)
natural language generation
(1)
feature attribution
(1)
embedding space
(1)
multilingual processing
(1)
out-of-distribution generalization
(1)
cross-lingual alignment
(1)
cross-domain learning
(1)
Papers
What is the Right Notion of Distance between Predict-then-Optimize Tasks?
UAI 2025
DDEQs: Distributional Deep Equilibrium Models through Wasserstein Gradient Flows
AISTATS 2025
Data Drives Unstable Hierarchical Generalization in LMs
EMNLP 2025
Investigating the interaction of linguistic and mathematical reasoning in language models using multilingual number puzzles
EMNLP 2025
Mixture of Parrots: Experts improve memorization more than reasoning
ICLR 2025
A Label is Worth A Thousand Images in Dataset Distillation
NIPS 2024
Tag-LLM: Repurposing General-Purpose LLMs for Specialized Domains
ICML 2024
Domain adaptation using optimal transport for invariant learning using histopathology datasets
MIDL 2023
InfoOT: Information Maximizing Optimal Transport
ICML 2023
Generating Synthetic Datasets by Interpolating along Generalized Geodesics
UAI 2023
Hierarchical Optimal Transport for Comparing Histopathology Datasets
MIDL 2022
Are GANs overkill for NLP?
NIPS 2022
Dataset Dynamics via Gradient Flows in Probability Space
ICML 2021
Unsupervised Hierarchy Matching with Optimal Transport over Hyperbolic Spaces
AISTATS 2020
Geometric Dataset Distances via Optimal Transport
NIPS 2020
Towards Optimal Transport with Global Invariances
AISTATS 2019
Towards Robust, Locally Linear Deep Networks
ICLR 2019
Learning Generative Models across Incomparable Spaces
ICML 2019
Functional Transparency for Structured Data: a Game-Theoretic Approach
ICML 2019
Towards Robust Interpretability with Self-Explaining Neural Networks
NIPS 2018
Gromov-Wasserstein Alignment of Word Embedding Spaces
EMNLP 2018
Structured Optimal Transport
AISTATS 2018
A causal framework for explaining the predictions of black-box sequence-to-sequence models
EMNLP 2017