Word, graph and manifold embedding from Markov processes. - Tatsunori B. Hashimoto; David Alvarez-Melis; Tommi S. Jaakkola (CoRR, 2015)

Topic Modeling in Twitter: Aggregating Tweets by Conversations. - David Alvarez-Melis; Martin Saveski (ICWSM, 2016)

Word Embeddings as Metric Recovery in Semantic Spaces. - Tatsunori B. Hashimoto; David Alvarez-Melis; Tommi S. Jaakkola (Trans. Assoc. Comput. Linguistics, 2016)

A causal framework for explaining the predictions of black-box sequence-to-sequence models. - David Alvarez-Melis; Tommi S. Jaakkola (EMNLP, 2017)

Tree-structured decoding with doubly-recurrent neural networks. - David Alvarez-Melis; Tommi S. Jaakkola (ICLR (Poster), 2017)

Structured Optimal Transport. - David Alvarez-Melis; Tommi S. Jaakkola; Stefanie Jegelka (AISTATS, 2018)

Gromov-Wasserstein Alignment of Word Embedding Spaces. - David Alvarez-Melis; Tommi S. Jaakkola (EMNLP, 2018)

Distributional Adversarial Networks. - Chengtao Li; David Alvarez-Melis; Keyulu Xu; Stefanie Jegelka; Suvrit Sra (ICLR (Workshop), 2018)

Towards Robust Interpretability with Self-Explaining Neural Networks. - David Alvarez-Melis; Tommi S. Jaakkola (NeurIPS, 2018)

On the Robustness of Interpretability Methods. - David Alvarez-Melis; Tommi S. Jaakkola (CoRR, 2018)

Game-Theoretic Interpretability for Temporal Modeling. - Guang-He Lee; David Alvarez-Melis; Tommi S. Jaakkola (CoRR, 2018)

Towards Optimal Transport with Global Invariances. - David Alvarez-Melis; Stefanie Jegelka; Tommi S. Jaakkola (AISTATS, 2019)

Towards Robust, Locally Linear Deep Networks. - Guang-He Lee; David Alvarez-Melis; Tommi S. Jaakkola (ICLR (Poster), 2019)

Learning Generative Models across Incomparable Spaces. - Charlotte Bunne; David Alvarez-Melis; Andreas Krause 001; Stefanie Jegelka (ICML, 2019)

Functional Transparency for Structured Data: a Game-Theoretic Approach. - Guang-He Lee; Wengong Jin; David Alvarez-Melis; Tommi S. Jaakkola (ICML, 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)

Probabilistic Bias Mitigation in Word Embeddings. - Hailey James-Sorenson; David Alvarez-Melis (CoRR, 2019)

Unsupervised Hierarchy Matching with Optimal Transport over Hyperbolic Spaces. - David Alvarez-Melis; Youssef Mroueh; Tommi S. Jaakkola (AISTATS, 2020)

Geometric Dataset Distances via Optimal Transport. - David Alvarez-Melis; Nicolò Fusi (NeurIPS, 2020)

Gradient Flows in Dataset Space. - David Alvarez-Melis; Nicolò Fusi (CoRR, 2020)

From Human Explanation to Model Interpretability: A Framework Based on Weight of Evidence. - David Alvarez-Melis; Harmanpreet Kaur; Hal Daumé III; Hanna M. Wallach; Jennifer Wortman Vaughan (HCOMP, 2021)

Dataset Dynamics via Gradient Flows in Probability Space. - David Alvarez-Melis; Nicolò Fusi (ICML, 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)

Hierarchical Optimal Transport for Comparing Histopathology Datasets. - Anna Yeaton; Rahul G. Krishnan; Rebecca J. Mieloszyk; David Alvarez-Melis; Grace Huynh (MIDL, 2022)

Are GANs overkill for NLP? - David Alvarez-Melis; Vikas Garg 001; Adam Kalai (NeurIPS, 2022)

Why GANs are overkill for NLP. - David Alvarez-Melis; Vikas Garg 001; Adam Tauman Kalai (CoRR, 2022)

Interpretable Distribution Shift Detection using Optimal Transport. - Neha Hulkund; Nicolò Fusi; Jennifer Wortman Vaughan; David Alvarez-Melis (CoRR, 2022)

Neural Unbalanced Optimal Transport via Cycle-Consistent Semi-Couplings. - Frederike Lübeck; Charlotte Bunne; Gabriele Gut; Jacobo Sarabia del Castillo; Lucas Pelkmans; David Alvarez-Melis (CoRR, 2022)

Budget-Constrained Bounds for Mini-Batch Estimation of Optimal Transport. - David Alvarez-Melis; Nicolò Fusi; Lester Mackey; Tal Wagner (CoRR, 2022)

Transfer RL via the Undo Maps Formalism. - Abhi Gupta; Ted Moskovitz; David Alvarez-Melis; Aldo Pacchiano (CoRR, 2022)

Optimizing Functionals on the Space of Probabilities with Input Convex Neural Networks. - David Alvarez-Melis; Yair Schiff; Youssef Mroueh (Trans. Mach. Learn. Res., 2022)

InfoOT: Information Maximizing Optimal Transport. - Ching-Yao Chuang; Stefanie Jegelka; David Alvarez-Melis (ICML, 2023)

Domain adaptation using optimal transport for invariant learning using histopathology datasets. - Kianoush Falahkheirkhah; Alex Xijie Lu; David Alvarez-Melis; Grace Huynh (MIDL, 2023)

Generating Synthetic Datasets by Interpolating along Generalized Geodesics. - Jiaojiao Fan; David Alvarez-Melis (UAI, 2023)

Tag-LLM: Repurposing General-Purpose LLMs for Specialized Domains. - Junhong Shen; Neil A. Tenenholtz; James Brian Hall; David Alvarez-Melis; Nicolò Fusi (ICML, 2024)

A Label is Worth A Thousand Images in Dataset Distillation. - Tian Qin; Zhiwei Deng; David Alvarez-Melis (NeurIPS, 2024)

Distributional Dataset Distillation with Subtask Decomposition. - Tian Qin; Zhiwei Deng; David Alvarez-Melis (CoRR, 2024)

Continuous Language Model Interpolation for Dynamic and Controllable Text Generation. - Sara Kangaslahti; David Alvarez-Melis (CoRR, 2024)

CharED: Character-wise Ensemble Decoding for Large Language Models. - Kevin Gu; Eva Tuecke; Dmitriy Katz; Raya Horesh; David Alvarez-Melis; Mikhail Yurochkin (CoRR, 2024)

Strongly Isomorphic Neural Optimal Transport Across Incomparable Spaces. - Athina Sotiropoulou; David Alvarez-Melis (CoRR, 2024)

Understanding the Role of Functional Diversity in Weight-Ensembling with Ingredient Selection and Multidimensional Scaling. - Alex Rojas; David Alvarez-Melis (CoRR, 2024)

Adapting Language Models via Token Translation. - Zhili Feng; Tanya Marwah; Nicolò Fusi; David Alvarez-Melis; Lester Mackey (CoRR, 2024)

Sometimes I am a Tree: Data Drives Unstable Hierarchical Generalization. - Tian Qin; Naomi Saphra; David Alvarez-Melis (CoRR, 2024)

DDEQs: Distributional Deep Equilibrium Models through Wasserstein Gradient Flows. - Jonathan Geuter; Clément Bonet; Anna Korba; David Alvarez-Melis (AISTATS, 2025)

Mixture of Parrots: Experts improve memorization more than reasoning. - Samy Jelassi; Clara Mohri; David Brandfonbrener; Alex Gu; Nikhil Vyas 001; Nikhil Anand; David Alvarez-Melis; Yuanzhi Li; Sham M. Kakade; Eran Malach (ICLR, 2025)

What is the Right Notion of Distance between Predict-then-Optimize Tasks? - Paula Rodriguez Diaz; Lingkai Kong; Kai Wang 040; David Alvarez-Melis; Milind Tambe (UAI, 2025)

Continuous Language Model Interpolation yields Dynamic and Controllable Text Generation. - Sara Kangaslahti; David Alvarez-Melis (Trans. Mach. Learn. Res., 2025)

Reliable and Responsible Foundation Models. - Xinyu Yang 002; Junlin Han; Rishi Bommasani; Jinqi Luo; Wenjie Qu 001; Wangchunshu Zhou; Adel Bibi; Xiyao Wang; Jaehong Yoon; Elias Stengel-Eskin; Shengbang Tong; Lingfeng Shen; et al. (Trans. Mach. Learn. Res., 2025)

IGDA: Interactive Graph Discovery through Large Language Model Agents. - Alex Havrilla; David Alvarez-Melis; Nicolò Fusi (CoRR, 2025)

Distributional Scaling Laws for Emergent Capabilities. - Rosie Zhao; Tian Qin; David Alvarez-Melis; Sham M. Kakade; Naomi Saphra (CoRR, 2025)

To Backtrack or Not to Backtrack: When Sequential Search Limits Model Reasoning. - Tian Qin; David Alvarez-Melis; Samy Jelassi; Eran Malach (CoRR, 2025)

Causal integration of chemical structures improves representations of microscopy images for morphological profiling. - Yemin Yu; Neil A. Tenenholtz; Lester Mackey; Ying Wei; David Alvarez-Melis; Ava P. Amini; Alex X. Lu (CoRR, 2025)

Decomposing Elements of Problem Solving: What "Math" Does RL Teach? - Tian Qin; Core Francisco Park; Mujin Kwun; Aaron Walsman; Eran Malach; Nikhil Anand; Hidenori Tanaka; David Alvarez-Melis (CoRR, 2025)

Guided Speculative Inference for Efficient Test-Time Alignment of LLMs. - Jonathan Geuter; Youssef Mroueh; David Alvarez-Melis (CoRR, 2025)

Investigating the interaction of linguistic and mathematical reasoning in language models using multilingual number puzzles. - Antara Raaghavi Bhattacharya; Isabel Papadimitriou; Kathryn Davidson; David Alvarez-Melis (CoRR, 2025)

Can Interpretation Predict Behavior on Unseen Data? - Victoria R. Li; Jenny Kaufmann; Martin Wattenberg; David Alvarez-Melis; Naomi Saphra (CoRR, 2025)

Bispectral OT: Dataset Comparison using Symmetry-Aware Optimal Transport. - Annabel Ma; Kaiying Hou; David Alvarez-Melis; Melanie Weber 001 (CoRR, 2025)

Boomerang Distillation Enables Zero-Shot Model Size Interpolation. - Sara Kangaslahti; Nihal V. Nayak; Jonathan Geuter; Marco Fumero; Francesco Locatello; David Alvarez-Melis (CoRR, 2025)

Adam or Gauss-Newton? A Comparative Study In Terms of Basis Alignment and SGD Noise. - Bingbin Liu; Rachit Bansal; Depen Morwani; Nikhil Vyas 001; David Alvarez-Melis; Sham M. Kakade (CoRR, 2025)